{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}\\isad.isadroot.ex.ac.uk\uoe\user\Submitted New Keynesian Model with Overtime Labor\Referee reports RESTAT\reports 2nd round\Files for RESTAT\NKPC_gmm_robustness.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}19 May 2012, 11:51:15
{txt}
{com}. 
. summarize overtimehours

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
overtimeho~s {c |}{res}       122     155.187    10.94078   138.6084   209.3205
{txt}
{com}. 
. generate A_h2fix= (real_GDP_percapita)/( (516*((N1_percapita_SA)^(1-0.33)) )+(155.187*((N2_percapita_SA)^(1-0.33)) ) )
{txt}(582 missing values generated)

{com}. 
. generate  overtime_share_h2fix= (comprnfb)/ (A_h2fix*((N2_percapita_SA)^(-0.33))  )
{txt}(582 missing values generated)

{com}. 
. drop overtime_share_h2fix
{txt}
{com}. 
. generate  overtime_share_h2fix= (comprnfb)/ (A_h2fix*((N2_percapita_SA)^(-0.33))  )* (100/200.8336)
{txt}(582 missing values generated)

{com}. 
. generate log_overtime_share_h2fix=log(overtime_share_h2fix)
{txt}(582 missing values generated)

{com}. 
. summarize log_overtime_share_h2fix

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
log_overti~x {c |}{res}       122    4.636248    .0312527   4.556129   4.697385
{txt}
{com}. 
. generate ROLC_h2fix= log_overtime_share_h2fix-4.636248
{txt}(582 missing values generated)

{com}. 
. generate  ROLC_h2fix_1= L.ROLC_h2fix
{txt}(582 missing values generated)

{com}. 
. generate  ROLC_h2fix_2= L.ROLC_h2fix_1
{txt}(582 missing values generated)

{com}. 
. generate  ROLC_h2fix_3= L.ROLC_h2fix_2
{txt}(582 missing values generated)

{com}. 
. generate  ROLC_h2fix_4= L.ROLC_h2fix_3
{txt}(582 missing values generated)

{com}. 
. ivregress gmm  pi_hat ( ROLC_h2fix pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 7     {col 56}Root MSE{col 70}= {res} .01029

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2}-.0352542{col 26}{space 2} .0166714{col 37}{space 1}   -2.11{col 46}{space 3}0.034{col 54}{space 4}-.0679295{col 67}{space 3} -.002579
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .9985568{col 26}{space 2} .0203076{col 37}{space 1}   49.17{col 46}{space 3}0.000{col 54}{space 4} .9587546{col 67}{space 3} 1.038359
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_h2fix pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 6 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}22{txt}) ={res} 10.1651{txt} (p = {res}0.9847{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
            ROLC_h2fix   pi_hat_F1
ROLC_h2fix {res}  .00027793
{txt} pi_hat_F1 {res}  3.749e-06    .0004124
{reset}
{com}. 
. ivreg2  pi_hat ( ROLC_h2fix pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant robust gmm2s nofooter bw(8) first ffirst
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_h2fix:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=8
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 24,    92) = {res}   36.75
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .1141142961{txt}{col 55}Centered R2   = {res}  0.5884
{txt}Total (uncentered) SS   = {res} .1141241428{txt}{col 55}Uncentered R2 = {res}  0.5885
{txt}Residual SS             = {res} .0469654465{txt}{col 55}Root MSE      = {res}  .02259

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}        ROLC_h2fix{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2}-.0682234{col 32}{space 2} .2738826{col 43}{space 1}   -0.25{col 52}{space 3}0.804{col 60}{space 4}-.6121778{col 73}{space 3}  .475731
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}-.3120998{col 32}{space 2} .3149013{col 43}{space 1}   -0.99{col 52}{space 3}0.324{col 60}{space 4}-.9375209{col 73}{space 3} .3133214
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .0604851{col 32}{space 2} .2133928{col 43}{space 1}    0.28{col 52}{space 3}0.777{col 60}{space 4}-.3633314{col 73}{space 3} .4843016
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1829311{col 32}{space 2} .1993797{col 43}{space 1}    0.92{col 52}{space 3}0.361{col 60}{space 4}-.2130541{col 73}{space 3} .5789163
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .3882938{col 32}{space 2} .1247446{col 43}{space 1}    3.11{col 52}{space 3}0.002{col 60}{space 4} .1405402{col 73}{space 3} .6360473
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2} .1118476{col 32}{space 2} .0786719{col 43}{space 1}    1.42{col 52}{space 3}0.158{col 60}{space 4}-.0444016{col 73}{space 3} .2680969
{txt}{space 6}ROLC_h2fix_3 {c |}{col 20}{res}{space 2} .2344741{col 32}{space 2} .0892835{col 43}{space 1}    2.63{col 52}{space 3}0.010{col 60}{space 4} .0571493{col 73}{space 3} .4117988
{txt}{space 6}ROLC_h2fix_4 {c |}{col 20}{res}{space 2} .0320926{col 32}{space 2} .0820196{col 43}{space 1}    0.39{col 52}{space 3}0.696{col 60}{space 4}-.1308055{col 73}{space 3} .1949907
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0733159{col 32}{space 2} .1000602{col 43}{space 1}    0.73{col 52}{space 3}0.466{col 60}{space 4}-.1254123{col 73}{space 3} .2720441
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0151538{col 32}{space 2} .0816824{col 43}{space 1}    0.19{col 52}{space 3}0.853{col 60}{space 4}-.1470746{col 73}{space 3} .1773821
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2} .0350861{col 32}{space 2} .0820162{col 43}{space 1}    0.43{col 52}{space 3}0.670{col 60}{space 4}-.1278051{col 73}{space 3} .1979773
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .1169026{col 32}{space 2} .0842797{col 43}{space 1}    1.39{col 52}{space 3}0.169{col 60}{space 4}-.0504843{col 73}{space 3} .2842894
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2}-.0754919{col 32}{space 2} .1311016{col 43}{space 1}   -0.58{col 52}{space 3}0.566{col 60}{space 4}-.3358709{col 73}{space 3} .1848871
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .1234822{col 32}{space 2} .1004176{col 43}{space 1}    1.23{col 52}{space 3}0.222{col 60}{space 4}-.0759558{col 73}{space 3} .3229202
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2}-.0356397{col 32}{space 2}  .099102{col 43}{space 1}   -0.36{col 52}{space 3}0.720{col 60}{space 4}-.2324648{col 73}{space 3} .1611853
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2} .2400979{col 32}{space 2} .1360512{col 43}{space 1}    1.76{col 52}{space 3}0.081{col 60}{space 4}-.0301115{col 73}{space 3} .5103072
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0011611{col 32}{space 2} .0038078{col 43}{space 1}    0.30{col 52}{space 3}0.761{col 60}{space 4}-.0064016{col 73}{space 3} .0087238
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0110204{col 32}{space 2} .0045722{col 43}{space 1}    2.41{col 52}{space 3}0.018{col 60}{space 4} .0019397{col 73}{space 3} .0201012
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2}-.0053649{col 32}{space 2} .0045663{col 43}{space 1}   -1.17{col 52}{space 3}0.243{col 60}{space 4}-.0144339{col 73}{space 3} .0037041
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2}-.0014164{col 32}{space 2} .0036141{col 43}{space 1}   -0.39{col 52}{space 3}0.696{col 60}{space 4}-.0085942{col 73}{space 3} .0057614
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .4467734{col 32}{space 2} .2355739{col 43}{space 1}    1.90{col 52}{space 3}0.061{col 60}{space 4}-.0210966{col 73}{space 3} .9146435
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}  -.55905{col 32}{space 2}   .36081{col 43}{space 1}   -1.55{col 52}{space 3}0.125{col 60}{space 4} -1.27565{col 73}{space 3} .1575498
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2} .9323381{col 32}{space 2} .4001723{col 43}{space 1}    2.33{col 52}{space 3}0.022{col 60}{space 4} .1375615{col 73}{space 3} 1.727115
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.6170085{col 32}{space 2}  .225674{col 43}{space 1}   -2.73{col 52}{space 3}0.008{col 60}{space 4}-1.065217{col 73}{space 3}-.1688005
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1
{col 23}ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2
{col 23}pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4
{col 23}longshort_spread_1 longshort_spread_2 longshort_spread_3
{col 23}longshort_spread_4 logy_detrended_1 logy_detrended_2
{col 23}logy_detrended_3 logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 24,    92) = {res}   36.75
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 23,    92) = {res}   17.39
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=8
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 24,    92) = {res}   77.17
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0579688024{txt}{col 55}Centered R2   = {res}  0.8637
{txt}Total (uncentered) SS   = {res} .0582406245{txt}{col 55}Uncentered R2 = {res}  0.8644
{txt}Residual SS             = {res} .0078984481{txt}{col 55}Root MSE      = {res} .009266

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2} .3396699{col 32}{space 2} .0910473{col 43}{space 1}    3.73{col 52}{space 3}0.000{col 60}{space 4} .1588421{col 73}{space 3} .5204978
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .1689073{col 32}{space 2} .1147409{col 43}{space 1}    1.47{col 52}{space 3}0.144{col 60}{space 4}-.0589782{col 73}{space 3} .3967927
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .3505861{col 32}{space 2} .0971555{col 43}{space 1}    3.61{col 52}{space 3}0.001{col 60}{space 4} .1576269{col 73}{space 3} .5435454
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2}-.0162771{col 32}{space 2} .0917149{col 43}{space 1}   -0.18{col 52}{space 3}0.860{col 60}{space 4}-.1984308{col 73}{space 3} .1658766
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .0822295{col 32}{space 2} .0392592{col 43}{space 1}    2.09{col 52}{space 3}0.039{col 60}{space 4} .0042574{col 73}{space 3} .1602017
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2}-.0052316{col 32}{space 2} .0278561{col 43}{space 1}   -0.19{col 52}{space 3}0.851{col 60}{space 4}-.0605562{col 73}{space 3} .0500929
{txt}{space 6}ROLC_h2fix_3 {c |}{col 20}{res}{space 2} .0008187{col 32}{space 2} .0271314{col 43}{space 1}    0.03{col 52}{space 3}0.976{col 60}{space 4}-.0530667{col 73}{space 3} .0547041
{txt}{space 6}ROLC_h2fix_4 {c |}{col 20}{res}{space 2}-.0222692{col 32}{space 2} .0422889{col 43}{space 1}   -0.53{col 52}{space 3}0.600{col 60}{space 4}-.1062586{col 73}{space 3} .0617202
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0646536{col 32}{space 2} .0287951{col 43}{space 1}    2.25{col 52}{space 3}0.027{col 60}{space 4} .0074641{col 73}{space 3} .1218431
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0206096{col 32}{space 2} .0327095{col 43}{space 1}    0.63{col 52}{space 3}0.530{col 60}{space 4}-.0443543{col 73}{space 3} .0855735
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2} .0061425{col 32}{space 2} .0322653{col 43}{space 1}    0.19{col 52}{space 3}0.849{col 60}{space 4}-.0579392{col 73}{space 3} .0702242
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0144935{col 32}{space 2} .0360154{col 43}{space 1}    0.40{col 52}{space 3}0.688{col 60}{space 4}-.0570363{col 73}{space 3} .0860232
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .0614175{col 32}{space 2} .0354357{col 43}{space 1}    1.73{col 52}{space 3}0.086{col 60}{space 4}-.0089609{col 73}{space 3} .1317959
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0721661{col 32}{space 2} .0613112{col 43}{space 1}    1.18{col 52}{space 3}0.242{col 60}{space 4}-.0496031{col 73}{space 3} .1939354
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} .0402707{col 32}{space 2} .0403677{col 43}{space 1}    1.00{col 52}{space 3}0.321{col 60}{space 4}-.0399031{col 73}{space 3} .1204444
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2}-.0225403{col 32}{space 2} .0422905{col 43}{space 1}   -0.53{col 52}{space 3}0.595{col 60}{space 4}-.1065329{col 73}{space 3} .0614524
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0018251{col 32}{space 2}  .003193{col 43}{space 1}    0.57{col 52}{space 3}0.569{col 60}{space 4}-.0045164{col 73}{space 3} .0081667
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0014959{col 32}{space 2} .0024375{col 43}{space 1}    0.61{col 52}{space 3}0.541{col 60}{space 4}-.0033452{col 73}{space 3} .0063371
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2}-.0036428{col 32}{space 2} .0032083{col 43}{space 1}   -1.14{col 52}{space 3}0.259{col 60}{space 4}-.0100148{col 73}{space 3} .0027291
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0029369{col 32}{space 2} .0021311{col 43}{space 1}    1.38{col 52}{space 3}0.172{col 60}{space 4}-.0012956{col 73}{space 3} .0071694
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .1240048{col 32}{space 2} .1676465{col 43}{space 1}    0.74{col 52}{space 3}0.461{col 60}{space 4}-.2089556{col 73}{space 3} .4569651
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.0789653{col 32}{space 2} .1594426{col 43}{space 1}   -0.50{col 52}{space 3}0.622{col 60}{space 4}-.3956321{col 73}{space 3} .2377015
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2}  .182247{col 32}{space 2} .1511653{col 43}{space 1}    1.21{col 52}{space 3}0.231{col 60}{space 4}-.1179803{col 73}{space 3} .4824744
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.1412137{col 32}{space 2} .1142794{col 43}{space 1}   -1.24{col 52}{space 3}0.220{col 60}{space 4}-.3681824{col 73}{space 3}  .085755
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1
{col 23}ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2
{col 23}pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4
{col 23}longshort_spread_1 longshort_spread_2 longshort_spread_3
{col 23}longshort_spread_4 logy_detrended_1 logy_detrended_2
{col 23}logy_detrended_3 logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 24,    92) = {res}   77.17
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 23,    92) = {res}   75.36
{txt}  Prob > F      = {res}  0.0000



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 24{txt},{res}    92{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 23{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 23{txt},{res}    92{txt})
{res}ROLC_h2fix  {col 14}{txt}|{col 18}{res}   36.75{col 28}  0.0000{col 37}{txt}|{col 42}{res}  504.30{col 51}  0.0000{col 60}{txt}|{col 65}{res}   17.39
pi_hat_F1   {col 14}{txt}|{col 18}{res}   77.17{col 28}  0.0000{col 37}{txt}|{col 42}{res} 2185.56{col 51}  0.0000{col 60}{txt}|{col 65}{res}   75.36

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.41
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.41
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.22
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.41
{txt}{col 36}10% maximal IV size{res}{col 67} 69.46
{txt}{col 36}15% maximal IV size{res}{col 67} 36.37
{txt}{col 36}20% maximal IV size{res}{col 67} 25.10
{txt}{col 36}25% maximal IV size{res}{col 67} 19.41
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}23{txt})={res}12.49  {col 61}{txt}P-val={res}0.9622

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    5.18
Kleibergen-Paap Wald rk F statistic{col 65}   13.60

{txt}Stock-Yogo weak ID test critical values for K1=2 and L1=24:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 20.69
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.05
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.06
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.32
{txt}{col 36}10% maximal IV size{res}{col 67} 53.39
{txt}{col 36}15% maximal IV size{res}{col 67} 28.42
{txt}{col 36}20% maximal IV size{res}{col 67} 19.97
{txt}{col 36}25% maximal IV size{res}{col 67} 15.64
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}24{txt},{res}92{txt})={col 49}{res} 123.31{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}24{txt})={col 49}{res}3731.38{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}24{txt})={col 49}{res}  10.41{col 61}{txt}P-val={res}0.9926

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       116
{txt}Number of regressors                 K  = {res}         2
{txt}Number of endogenous regressors      K1 = {res}         2
{txt}Number of instruments                L  = {res}        24
{txt}Number of excluded instruments       L1 = {res}        24

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=8
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F(  2,   114) = {res} 1460.77
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0581346117{txt}{col 55}Centered R2   = {res}  0.7888
{txt}Total (uncentered) SS   = {res} .0584658598{txt}{col 55}Uncentered R2 = {res}  0.7900
{txt}Residual SS             = {res} .0122780228{txt}{col 55}Root MSE      = {res}  .01029

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2}-.0352542{col 26}{space 2} .0152759{col 37}{space 1}   -2.31{col 46}{space 3}0.021{col 54}{space 4}-.0651944{col 67}{space 3} -.005314
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .9985568{col 26}{space 2} .0183656{col 37}{space 1}   54.37{col 46}{space 3}0.000{col 54}{space 4} .9625608{col 67}{space 3} 1.034553
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ivregress gmm  pi_hat ( ROLC_h2fix pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 2     {col 56}Root MSE{col 70}= {res} .01047

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2}-.0263163{col 26}{space 2} .0243568{col 37}{space 1}   -1.08{col 46}{space 3}0.280{col 54}{space 4}-.0740547{col 67}{space 3}  .021422
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} 1.027994{col 26}{space 2} .0262742{col 37}{space 1}   39.13{col 46}{space 3}0.000{col 54}{space 4} .9764977{col 67}{space 3} 1.079491
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_h2fix pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 19 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}12{txt}) ={res} 12.1721{txt} (p = {res}0.4320{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
            ROLC_h2fix   pi_hat_F1
ROLC_h2fix {res}  .00059325
{txt} pi_hat_F1 {res}  .00009463   .00069033
{reset}
{com}. 
. ivreg2  pi_hat ( ROLC_h2fix pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 pi_w_1 pi_w_2  pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant robust gmm2s nofooter bw(3) first ffirst
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_h2fix:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=3
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 14,   102) = {res}   15.24
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .1141142961{txt}{col 55}Centered R2   = {res}  0.5039
{txt}Total (uncentered) SS   = {res} .1141241428{txt}{col 55}Uncentered R2 = {res}  0.5040
{txt}Residual SS             = {res} .0566095244{txt}{col 55}Root MSE      = {res}  .02356

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}        ROLC_h2fix{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2}-.0975111{col 32}{space 2} .3157347{col 43}{space 1}   -0.31{col 52}{space 3}0.758{col 60}{space 4}-.7237693{col 73}{space 3} .5287471
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}-.2008248{col 32}{space 2} .3752156{col 43}{space 1}   -0.54{col 52}{space 3}0.594{col 60}{space 4}-.9450632{col 73}{space 3} .5434136
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .0839145{col 32}{space 2} .2361262{col 43}{space 1}    0.36{col 52}{space 3}0.723{col 60}{space 4}-.3844408{col 73}{space 3} .5522697
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .2879905{col 32}{space 2} .2107998{col 43}{space 1}    1.37{col 52}{space 3}0.175{col 60}{space 4}  -.13013{col 73}{space 3}  .706111
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .3966653{col 32}{space 2} .1067062{col 43}{space 1}    3.72{col 52}{space 3}0.000{col 60}{space 4} .1850141{col 73}{space 3} .6083166
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2} .2253196{col 32}{space 2} .0828838{col 43}{space 1}    2.72{col 52}{space 3}0.008{col 60}{space 4}   .06092{col 73}{space 3} .3897191
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0984928{col 32}{space 2}  .089049{col 43}{space 1}    1.11{col 52}{space 3}0.271{col 60}{space 4}-.0781354{col 73}{space 3}  .275121
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0381438{col 32}{space 2} .0793504{col 43}{space 1}    0.48{col 52}{space 3}0.632{col 60}{space 4}-.1192474{col 73}{space 3}  .195535
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2}-.0311676{col 32}{space 2} .1014775{col 43}{space 1}   -0.31{col 52}{space 3}0.759{col 60}{space 4}-.2324478{col 73}{space 3} .1701126
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2}  .148795{col 32}{space 2} .1170973{col 43}{space 1}    1.27{col 52}{space 3}0.207{col 60}{space 4}-.0834669{col 73}{space 3}  .381057
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0028854{col 32}{space 2} .0048091{col 43}{space 1}    0.60{col 52}{space 3}0.550{col 60}{space 4}-.0066534{col 73}{space 3} .0124242
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0035757{col 32}{space 2} .0046735{col 43}{space 1}    0.77{col 52}{space 3}0.446{col 60}{space 4}-.0056942{col 73}{space 3} .0128456
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .5068041{col 32}{space 2}  .306295{col 43}{space 1}    1.65{col 52}{space 3}0.101{col 60}{space 4}-.1007306{col 73}{space 3} 1.114339
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.1696576{col 32}{space 2} .3053181{col 43}{space 1}   -0.56{col 52}{space 3}0.580{col 60}{space 4}-.7752546{col 73}{space 3} .4359394
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1
{col 23}ROLC_h2fix_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2
{col 23}longshort_spread_1 longshort_spread_2 logy_detrended_1
{col 23}logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 14,   102) = {res}   15.24
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 13,   102) = {res}   12.72
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=3
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 14,   102) = {res}   20.91
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0579688024{txt}{col 55}Centered R2   = {res}  0.8534
{txt}Total (uncentered) SS   = {res} .0582406245{txt}{col 55}Uncentered R2 = {res}  0.8541
{txt}Residual SS             = {res} .0084999311{txt}{col 55}Root MSE      = {res} .009129

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2} .3372418{col 32}{space 2} .1221061{col 43}{space 1}    2.76{col 52}{space 3}0.007{col 60}{space 4}  .095045{col 73}{space 3} .5794386
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .2056935{col 32}{space 2} .1091019{col 43}{space 1}    1.89{col 52}{space 3}0.062{col 60}{space 4}-.0107096{col 73}{space 3} .4220967
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .3769079{col 32}{space 2} .1004399{col 43}{space 1}    3.75{col 52}{space 3}0.000{col 60}{space 4} .1776859{col 73}{space 3} .5761299
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} -.068108{col 32}{space 2} .0828551{col 43}{space 1}   -0.82{col 52}{space 3}0.413{col 60}{space 4}-.2324507{col 73}{space 3} .0962346
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .0608431{col 32}{space 2} .0310079{col 43}{space 1}    1.96{col 52}{space 3}0.052{col 60}{space 4}-.0006609{col 73}{space 3}  .122347
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2}-.0013943{col 32}{space 2} .0300691{col 43}{space 1}   -0.05{col 52}{space 3}0.963{col 60}{space 4}-.0610361{col 73}{space 3} .0582476
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2}  .055933{col 32}{space 2} .0329206{col 43}{space 1}    1.70{col 52}{space 3}0.092{col 60}{space 4} -.009365{col 73}{space 3} .1212309
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0151263{col 32}{space 2} .0338788{col 43}{space 1}    0.45{col 52}{space 3}0.656{col 60}{space 4}-.0520721{col 73}{space 3} .0823248
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .0496143{col 32}{space 2}  .038229{col 43}{space 1}    1.30{col 52}{space 3}0.197{col 60}{space 4}-.0262128{col 73}{space 3} .1254415
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2}  .069816{col 32}{space 2} .0606824{col 43}{space 1}    1.15{col 52}{space 3}0.253{col 60}{space 4}-.0505474{col 73}{space 3} .1901793
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0015648{col 32}{space 2} .0035097{col 43}{space 1}    0.45{col 52}{space 3}0.657{col 60}{space 4}-.0053968{col 73}{space 3} .0085263
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0007064{col 32}{space 2} .0031939{col 43}{space 1}    0.22{col 52}{space 3}0.825{col 60}{space 4}-.0056288{col 73}{space 3} .0070415
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .0941574{col 32}{space 2} .1689218{col 43}{space 1}    0.56{col 52}{space 3}0.578{col 60}{space 4}-.2408983{col 73}{space 3}  .429213
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}  .013765{col 32}{space 2} .1737774{col 43}{space 1}    0.08{col 52}{space 3}0.937{col 60}{space 4}-.3309216{col 73}{space 3} .3584517
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1
{col 23}ROLC_h2fix_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2
{col 23}longshort_spread_1 longshort_spread_2 logy_detrended_1
{col 23}logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 14,   102) = {res}   20.91
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 13,   102) = {res}   21.97
{txt}  Prob > F      = {res}  0.0000



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 14{txt},{res}   102{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 13{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 13{txt},{res}   102{txt})
{res}ROLC_h2fix  {col 14}{txt}|{col 18}{res}   15.24{col 28}  0.0000{col 37}{txt}|{col 42}{res}  188.13{col 51}  0.0000{col 60}{txt}|{col 65}{res}   12.72
pi_hat_F1   {col 14}{txt}|{col 18}{res}   20.91{col 28}  0.0000{col 37}{txt}|{col 42}{res}  324.81{col 51}  0.0000{col 60}{txt}|{col 65}{res}   21.97

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.18
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.52
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.49
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.71
{txt}{col 36}10% maximal IV size{res}{col 67} 45.64
{txt}{col 36}15% maximal IV size{res}{col 67} 24.42
{txt}{col 36}20% maximal IV size{res}{col 67} 17.14
{txt}{col 36}25% maximal IV size{res}{col 67} 13.41
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}13{txt})={res}18.26  {col 61}{txt}P-val={res}0.1480

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    6.97
Kleibergen-Paap Wald rk F statistic{col 65}   10.45

{txt}Stock-Yogo weak ID test critical values for K1=2 and L1=14:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 19.83
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 10.89
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.20
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.53
{txt}{col 36}10% maximal IV size{res}{col 67} 36.36
{txt}{col 36}15% maximal IV size{res}{col 67} 19.72
{txt}{col 36}20% maximal IV size{res}{col 67} 14.05
{txt}{col 36}25% maximal IV size{res}{col 67} 11.13
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}14{txt},{res}102{txt})={col 49}{res}  53.71{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}14{txt})={col 49}{res} 855.22{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}14{txt})={col 49}{res}  14.65{col 61}{txt}P-val={res}0.4027

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       116
{txt}Number of regressors                 K  = {res}         2
{txt}Number of endogenous regressors      K1 = {res}         2
{txt}Number of instruments                L  = {res}        14
{txt}Number of excluded instruments       L1 = {res}        14

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=3
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F(  2,   114) = {res}  345.37
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0581346117{txt}{col 55}Centered R2   = {res}  0.7814
{txt}Total (uncentered) SS   = {res} .0584658598{txt}{col 55}Uncentered R2 = {res}  0.7827
{txt}Residual SS             = {res} .0127068021{txt}{col 55}Root MSE      = {res}  .01047

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2}-.0263163{col 26}{space 2} .0259724{col 37}{space 1}   -1.01{col 46}{space 3}0.311{col 54}{space 4}-.0772213{col 67}{space 3} .0245886
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} 1.027994{col 26}{space 2} .0387768{col 37}{space 1}   26.51{col 46}{space 3}0.000{col 54}{space 4} .9519931{col 67}{space 3} 1.103995
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ivregress gmm  pi_hat ( ROLC_h2fix pi_hat_1  pi_hat_F1= pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}3{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 13    {col 56}Root MSE{col 70}= {res} .00913

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2} .0369121{col 26}{space 2} .0157027{col 37}{space 1}    2.35{col 46}{space 3}0.019{col 54}{space 4} .0061355{col 67}{space 3} .0676888
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .6841411{col 26}{space 2} .0756589{col 37}{space 1}    9.04{col 46}{space 3}0.000{col 54}{space 4} .5358523{col 67}{space 3} .8324298
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .2946245{col 26}{space 2} .0823039{col 37}{space 1}    3.58{col 46}{space 3}0.000{col 54}{space 4} .1333119{col 67}{space 3} .4559371
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_h2fix pi_hat_1 pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 20 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}20{txt}) ={res} 8.23469{txt} (p = {res}0.9902{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[3,3]
            ROLC_h2fix    pi_hat_1   pi_hat_F1
ROLC_h2fix {res}  .00024657
{txt}  pi_hat_1 {res}  .00096469   .00572427
{txt} pi_hat_F1 {res} -.00102574  -.00618443   .00677392
{reset}
{com}. 
. ivreg2  pi_hat ( ROLC_h2fix pi_hat_1  pi_hat_F1= pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant robust gmm2s nofooter bw(14) first ffirst
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_h2fix:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=14
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 23,    93) = {res}   57.50
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .1141142961{txt}{col 55}Centered R2   = {res}  0.5882
{txt}Total (uncentered) SS   = {res} .1141241428{txt}{col 55}Uncentered R2 = {res}  0.5882
{txt}Residual SS             = {res} .0469946788{txt}{col 55}Root MSE      = {res}  .02248

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}        ROLC_h2fix{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}-.3289628{col 32}{space 2} .3679917{col 43}{space 1}   -0.89{col 52}{space 3}0.374{col 60}{space 4}-1.059721{col 73}{space 3} .4017959
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .0412841{col 32}{space 2} .1804425{col 43}{space 1}    0.23{col 52}{space 3}0.820{col 60}{space 4}-.3170389{col 73}{space 3} .3996071
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1719094{col 32}{space 2} .1888849{col 43}{space 1}    0.91{col 52}{space 3}0.365{col 60}{space 4}-.2031785{col 73}{space 3} .5469974
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .3889123{col 32}{space 2} .1054809{col 43}{space 1}    3.69{col 52}{space 3}0.000{col 60}{space 4} .1794481{col 73}{space 3} .5983765
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2} .1100087{col 32}{space 2} .0735731{col 43}{space 1}    1.50{col 52}{space 3}0.138{col 60}{space 4}-.0360929{col 73}{space 3} .2561103
{txt}{space 6}ROLC_h2fix_3 {c |}{col 20}{res}{space 2} .2315765{col 32}{space 2}  .079856{col 43}{space 1}    2.90{col 52}{space 3}0.005{col 60}{space 4} .0729983{col 73}{space 3} .3901546
{txt}{space 6}ROLC_h2fix_4 {c |}{col 20}{res}{space 2} .0346571{col 32}{space 2} .0675493{col 43}{space 1}    0.51{col 52}{space 3}0.609{col 60}{space 4}-.0994823{col 73}{space 3} .1687965
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0709123{col 32}{space 2} .0965346{col 43}{space 1}    0.73{col 52}{space 3}0.464{col 60}{space 4}-.1207863{col 73}{space 3}  .262611
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0120466{col 32}{space 2} .0672614{col 43}{space 1}    0.18{col 52}{space 3}0.858{col 60}{space 4}-.1215211{col 73}{space 3} .1456143
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2} .0365189{col 32}{space 2} .0783984{col 43}{space 1}    0.47{col 52}{space 3}0.642{col 60}{space 4}-.1191648{col 73}{space 3} .1922027
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .1154837{col 32}{space 2} .0705817{col 43}{space 1}    1.64{col 52}{space 3}0.105{col 60}{space 4}-.0246775{col 73}{space 3} .2556449
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2}-.0874655{col 32}{space 2} .1331158{col 43}{space 1}   -0.66{col 52}{space 3}0.513{col 60}{space 4}-.3518072{col 73}{space 3} .1768761
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .1194877{col 32}{space 2} .0853342{col 43}{space 1}    1.40{col 52}{space 3}0.165{col 60}{space 4}-.0499691{col 73}{space 3} .2889446
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2}-.0360039{col 32}{space 2}  .097797{col 43}{space 1}   -0.37{col 52}{space 3}0.714{col 60}{space 4}-.2302094{col 73}{space 3} .1582016
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2} .2395239{col 32}{space 2} .1315704{col 43}{space 1}    1.82{col 52}{space 3}0.072{col 60}{space 4}-.0217488{col 73}{space 3} .5007967
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0012235{col 32}{space 2} .0035714{col 43}{space 1}    0.34{col 52}{space 3}0.733{col 60}{space 4}-.0058686{col 73}{space 3} .0083156
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0109511{col 32}{space 2} .0042549{col 43}{space 1}    2.57{col 52}{space 3}0.012{col 60}{space 4} .0025016{col 73}{space 3} .0194005
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2}-.0054048{col 32}{space 2} .0040953{col 43}{space 1}   -1.32{col 52}{space 3}0.190{col 60}{space 4}-.0135372{col 73}{space 3} .0027275
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2}-.0014387{col 32}{space 2} .0030977{col 43}{space 1}   -0.46{col 52}{space 3}0.643{col 60}{space 4}-.0075901{col 73}{space 3} .0047127
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .4565819{col 32}{space 2} .2231661{col 43}{space 1}    2.05{col 52}{space 3}0.044{col 60}{space 4} .0134183{col 73}{space 3} .8997455
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.5756188{col 32}{space 2} .3513928{col 43}{space 1}   -1.64{col 52}{space 3}0.105{col 60}{space 4}-1.273415{col 73}{space 3} .1221777
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2} .9460104{col 32}{space 2} .3833737{col 43}{space 1}    2.47{col 52}{space 3}0.015{col 60}{space 4} .1847062{col 73}{space 3} 1.707315
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.6244157{col 32}{space 2} .1823443{col 43}{space 1}   -3.42{col 52}{space 3}0.001{col 60}{space 4}-.9865153{col 73}{space 3}-.2623161
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2
{col 23}ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4
{col 23}pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1
{col 23}longshort_spread_2 longshort_spread_3 longshort_spread_4
{col 23}logy_detrended_1 logy_detrended_2 logy_detrended_3
{col 23}logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 23,    93) = {res}   57.50
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 21,    93) = {res}   32.88
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=14
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 23,    93) = {res}  261.73
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0586060405{txt}{col 55}Centered R2   = {res}  0.8928
{txt}Total (uncentered) SS   = {res} .0590151024{txt}{col 55}Uncentered R2 = {res}  0.8936
{txt}Residual SS             = {res} .0062805346{txt}{col 55}Root MSE      = {res} .008218

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          pi_hat_1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .2471737{col 32}{space 2} .1012955{col 43}{space 1}    2.44{col 52}{space 3}0.017{col 60}{space 4} .0460209{col 73}{space 3} .4483264
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .2814436{col 32}{space 2}  .107919{col 43}{space 1}    2.61{col 52}{space 3}0.011{col 60}{space 4} .0671378{col 73}{space 3} .4957493
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1615528{col 32}{space 2}  .062903{col 43}{space 1}    2.57{col 52}{space 3}0.012{col 60}{space 4} .0366398{col 73}{space 3} .2864657
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2}-.0090656{col 32}{space 2} .0421666{col 43}{space 1}   -0.21{col 52}{space 3}0.830{col 60}{space 4}-.0928002{col 73}{space 3}  .074669
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2} .0269545{col 32}{space 2} .0230303{col 43}{space 1}    1.17{col 52}{space 3}0.245{col 60}{space 4}-.0187792{col 73}{space 3} .0726882
{txt}{space 6}ROLC_h2fix_3 {c |}{col 20}{res}{space 2} .0424727{col 32}{space 2} .0412564{col 43}{space 1}    1.03{col 52}{space 3}0.306{col 60}{space 4}-.0394542{col 73}{space 3} .1243997
{txt}{space 6}ROLC_h2fix_4 {c |}{col 20}{res}{space 2}-.0375893{col 32}{space 2} .0437883{col 43}{space 1}   -0.86{col 52}{space 3}0.393{col 60}{space 4}-.1245442{col 73}{space 3} .0493656
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0352312{col 32}{space 2} .0262478{col 43}{space 1}    1.34{col 52}{space 3}0.183{col 60}{space 4}-.0168917{col 73}{space 3}  .087354
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0455437{col 32}{space 2} .0365063{col 43}{space 1}    1.25{col 52}{space 3}0.215{col 60}{space 4}-.0269507{col 73}{space 3}  .118038
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2}-.0210026{col 32}{space 2}  .026067{col 43}{space 1}   -0.81{col 52}{space 3}0.422{col 60}{space 4}-.0727664{col 73}{space 3} .0307613
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0207969{col 32}{space 2} .0254864{col 43}{space 1}    0.82{col 52}{space 3}0.417{col 60}{space 4}-.0298141{col 73}{space 3} .0714079
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1755063{col 32}{space 2} .0259441{col 43}{space 1}    6.76{col 52}{space 3}0.000{col 60}{space 4} .1239865{col 73}{space 3}  .227026
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0585499{col 32}{space 2} .0340763{col 43}{space 1}    1.72{col 52}{space 3}0.089{col 60}{space 4} -.009119{col 73}{space 3} .1262187
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} .0053373{col 32}{space 2} .0168174{col 43}{space 1}    0.32{col 52}{space 3}0.752{col 60}{space 4}-.0280588{col 73}{space 3} .0387333
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2} .0084123{col 32}{space 2}  .030953{col 43}{space 1}    0.27{col 52}{space 3}0.786{col 60}{space 4}-.0530543{col 73}{space 3} .0698789
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2}-.0009143{col 32}{space 2}  .001751{col 43}{space 1}   -0.52{col 52}{space 3}0.603{col 60}{space 4}-.0043914{col 73}{space 3} .0025628
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0010166{col 32}{space 2} .0017488{col 43}{space 1}    0.58{col 52}{space 3}0.562{col 60}{space 4}-.0024562{col 73}{space 3} .0044895
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2} .0005852{col 32}{space 2}  .002678{col 43}{space 1}    0.22{col 52}{space 3}0.827{col 60}{space 4}-.0047328{col 73}{space 3} .0059033
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0003277{col 32}{space 2} .0021843{col 43}{space 1}    0.15{col 52}{space 3}0.881{col 60}{space 4}  -.00401{col 73}{space 3} .0046653
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2}-.1437699{col 32}{space 2} .1582508{col 43}{space 1}   -0.91{col 52}{space 3}0.366{col 60}{space 4}-.4580247{col 73}{space 3} .1704849
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} .2428607{col 32}{space 2} .1542258{col 43}{space 1}    1.57{col 52}{space 3}0.119{col 60}{space 4}-.0634013{col 73}{space 3} .5491227
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2}-.2004048{col 32}{space 2} .2036866{col 43}{space 1}   -0.98{col 52}{space 3}0.328{col 60}{space 4}-.6048861{col 73}{space 3} .2040765
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2} .1085724{col 32}{space 2} .1707254{col 43}{space 1}    0.64{col 52}{space 3}0.526{col 60}{space 4}-.2304544{col 73}{space 3} .4475991
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2
{col 23}ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4
{col 23}pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1
{col 23}longshort_spread_2 longshort_spread_3 longshort_spread_4
{col 23}logy_detrended_1 logy_detrended_2 logy_detrended_3
{col 23}logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 23,    93) = {res}  261.73
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 21,    93) = {res}   11.80
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=14
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 23,    93) = {res}  149.76
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0579688024{txt}{col 55}Centered R2   = {res}  0.8512
{txt}Total (uncentered) SS   = {res} .0582406245{txt}{col 55}Uncentered R2 = {res}  0.8519
{txt}Residual SS             = {res} .0086230689{txt}{col 55}Root MSE      = {res} .009629

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .2528647{col 32}{space 2} .1141588{col 43}{space 1}    2.22{col 52}{space 3}0.029{col 60}{space 4}  .026168{col 73}{space 3} .4795614
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .4461841{col 32}{space 2} .1007291{col 43}{space 1}    4.43{col 52}{space 3}0.000{col 60}{space 4}  .246156{col 73}{space 3} .6462122
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .0385975{col 32}{space 2} .0949188{col 43}{space 1}    0.41{col 52}{space 3}0.685{col 60}{space 4}-.1498924{col 73}{space 3} .2270873
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .0791502{col 32}{space 2} .0409589{col 43}{space 1}    1.93{col 52}{space 3}0.056{col 60}{space 4} -.002186{col 73}{space 3} .1604865
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2}  .003924{col 32}{space 2} .0262233{col 43}{space 1}    0.15{col 52}{space 3}0.881{col 60}{space 4}-.0481503{col 73}{space 3} .0559983
{txt}{space 6}ROLC_h2fix_3 {c |}{col 20}{res}{space 2} .0152454{col 32}{space 2} .0317894{col 43}{space 1}    0.48{col 52}{space 3}0.633{col 60}{space 4} -.047882{col 73}{space 3} .0783728
{txt}{space 6}ROLC_h2fix_4 {c |}{col 20}{res}{space 2}-.0350371{col 32}{space 2} .0449415{col 43}{space 1}   -0.78{col 52}{space 3}0.438{col 60}{space 4} -.124282{col 73}{space 3} .0542077
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0766206{col 32}{space 2} .0262352{col 43}{space 1}    2.92{col 52}{space 3}0.004{col 60}{space 4} .0245227{col 73}{space 3} .1287185
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0360794{col 32}{space 2} .0271455{col 43}{space 1}    1.33{col 52}{space 3}0.187{col 60}{space 4}-.0178261{col 73}{space 3}  .089985
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2}-.0009915{col 32}{space 2}  .034733{col 43}{space 1}   -0.03{col 52}{space 3}0.977{col 60}{space 4}-.0699644{col 73}{space 3} .0679815
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0215576{col 32}{space 2} .0388105{col 43}{space 1}    0.56{col 52}{space 3}0.580{col 60}{space 4}-.0555124{col 73}{space 3} .0986275
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1210317{col 32}{space 2} .0331981{col 43}{space 1}    3.65{col 52}{space 3}0.000{col 60}{space 4} .0551069{col 73}{space 3} .1869564
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0920538{col 32}{space 2}  .060802{col 43}{space 1}    1.51{col 52}{space 3}0.133{col 60}{space 4} -.028687{col 73}{space 3} .2127945
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} .0420836{col 32}{space 2} .0427947{col 43}{space 1}    0.98{col 52}{space 3}0.328{col 60}{space 4}-.0428983{col 73}{space 3} .1270654
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2}-.0196829{col 32}{space 2} .0479375{col 43}{space 1}   -0.41{col 52}{space 3}0.682{col 60}{space 4}-.1148772{col 73}{space 3} .0755115
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0015146{col 32}{space 2} .0028197{col 43}{space 1}    0.54{col 52}{space 3}0.592{col 60}{space 4}-.0040847{col 73}{space 3} .0071139
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0018412{col 32}{space 2} .0016234{col 43}{space 1}    1.13{col 52}{space 3}0.260{col 60}{space 4}-.0013824{col 73}{space 3} .0050649
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2} -.003444{col 32}{space 2} .0022656{col 43}{space 1}   -1.52{col 52}{space 3}0.132{col 60}{space 4}-.0079431{col 73}{space 3}  .001055
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0030482{col 32}{space 2} .0021182{col 43}{space 1}    1.44{col 52}{space 3}0.153{col 60}{space 4} -.001158{col 73}{space 3} .0072545
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .0751705{col 32}{space 2} .1586729{col 43}{space 1}    0.47{col 52}{space 3}0.637{col 60}{space 4}-.2399224{col 73}{space 3} .3902633
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} .0035272{col 32}{space 2} .1370545{col 43}{space 1}    0.03{col 52}{space 3}0.980{col 60}{space 4}-.2686359{col 73}{space 3} .2756903
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2} .1141756{col 32}{space 2} .1545942{col 43}{space 1}    0.74{col 52}{space 3}0.462{col 60}{space 4}-.1928179{col 73}{space 3}  .421169
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.1043349{col 32}{space 2} .1271303{col 43}{space 1}   -0.82{col 52}{space 3}0.414{col 60}{space 4}-.3567906{col 73}{space 3} .1481207
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2
{col 23}ROLC_h2fix_3 ROLC_h2fix_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4
{col 23}pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1
{col 23}longshort_spread_2 longshort_spread_3 longshort_spread_4
{col 23}logy_detrended_1 logy_detrended_2 logy_detrended_3
{col 23}logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 23,    93) = {res}  149.76
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 21,    93) = {res}    5.40
{txt}  Prob > F      = {res}  0.0000



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 23{txt},{res}    93{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 21{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 21{txt},{res}    93{txt})
{res}ROLC_h2fix  {col 14}{txt}|{col 18}{res}   57.50{col 28}  0.0000{col 37}{txt}|{col 42}{res}  861.34{col 51}  0.0000{col 60}{txt}|{col 65}{res}   32.88
pi_hat_1    {col 14}{txt}|{col 18}{res}  261.73{col 28}  0.0000{col 37}{txt}|{col 42}{res}  309.07{col 51}  0.0000{col 60}{txt}|{col 65}{res}   11.80
pi_hat_F1   {col 14}{txt}|{col 18}{res}  149.76{col 28}  0.0000{col 37}{txt}|{col 42}{res}  141.43{col 51}  0.0000{col 60}{txt}|{col 65}{res}    5.40

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.41
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.44
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.26
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.46
{txt}{col 36}10% maximal IV size{res}{col 67} 64.69
{txt}{col 36}15% maximal IV size{res}{col 67} 33.97
{txt}{col 36}20% maximal IV size{res}{col 67} 23.50
{txt}{col 36}25% maximal IV size{res}{col 67} 18.20
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}21{txt})={res}8.37   {col 61}{txt}P-val={res}0.9934

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    0.74
Kleibergen-Paap Wald rk F statistic{col 65}    4.34

{txt}Stock-Yogo weak ID test critical values for K1=3 and L1=23:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 19.86
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 10.68
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  5.92
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.25
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}23{txt},{res}93{txt})={col 49}{res} 159.33{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}23{txt})={col 49}{res}4570.91{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}23{txt})={col 49}{res}   7.61{col 61}{txt}P-val={res}0.9989

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       116
{txt}Number of regressors                 K  = {res}         3
{txt}Number of endogenous regressors      K1 = {res}         3
{txt}Number of instruments                L  = {res}        23
{txt}Number of excluded instruments       L1 = {res}        23

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=14
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F(  3,   113) = {res} 2283.73
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0581346117{txt}{col 55}Centered R2   = {res}  0.8335
{txt}Total (uncentered) SS   = {res} .0584658598{txt}{col 55}Uncentered R2 = {res}  0.8345
{txt}Residual SS             = {res} .0096780902{txt}{col 55}Root MSE      = {res} .009134

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2} .0369121{col 26}{space 2} .0164606{col 37}{space 1}    2.24{col 46}{space 3}0.025{col 54}{space 4}   .00465{col 67}{space 3} .0691742
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .6841411{col 26}{space 2} .0769756{col 37}{space 1}    8.89{col 46}{space 3}0.000{col 54}{space 4} .5332716{col 67}{space 3} .8350106
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .2946245{col 26}{space 2} .0833562{col 37}{space 1}    3.53{col 46}{space 3}0.000{col 54}{space 4} .1312494{col 67}{space 3} .4579997
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ivregress gmm  pi_hat ( ROLC_h2fix pi_hat_1 pi_hat_F1=  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}3{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 9     {col 56}Root MSE{col 70}= {res} .00951

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2} .0540934{col 26}{space 2} .0271438{col 37}{space 1}    1.99{col 46}{space 3}0.046{col 54}{space 4} .0008925{col 67}{space 3} .1072944
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .7969999{col 26}{space 2} .1114757{col 37}{space 1}    7.15{col 46}{space 3}0.000{col 54}{space 4} .5785114{col 67}{space 3} 1.015488
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .1811955{col 26}{space 2} .1189335{col 37}{space 1}    1.52{col 46}{space 3}0.128{col 54}{space 4}-.0519099{col 67}{space 3}  .414301
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_h2fix pi_hat_1 pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 20 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}10{txt}) ={res}  6.6703{txt} (p = {res}0.7562{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[3,3]
            ROLC_h2fix    pi_hat_1   pi_hat_F1
ROLC_h2fix {res}  .00073679
{txt}  pi_hat_1 {res}  .00265741   .01242684
{txt} pi_hat_F1 {res} -.00278741  -.01319698   .01414519
{reset}
{com}. 
. ivreg2  pi_hat ( ROLC_h2fix pi_hat_1 pi_hat_F1=  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2 pi_w_1 pi_w_2  pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant robust gmm2s nofooter bw(10) first ffirst
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_h2fix:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=10
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 13,   103) = {res}   22.95
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .1141142961{txt}{col 55}Centered R2   = {res}  0.5034
{txt}Total (uncentered) SS   = {res} .1141241428{txt}{col 55}Uncentered R2 = {res}  0.5034
{txt}Residual SS             = {res}  .056671304{txt}{col 55}Root MSE      = {res}  .02346

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}        ROLC_h2fix{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}-.2241955{col 32}{space 2} .3485873{col 43}{space 1}   -0.64{col 52}{space 3}0.522{col 60}{space 4}-.9155362{col 73}{space 3} .4671452
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .0558237{col 32}{space 2} .1820717{col 43}{space 1}    0.31{col 52}{space 3}0.760{col 60}{space 4}-.3052726{col 73}{space 3} .4169199
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .2712833{col 32}{space 2} .1621007{col 43}{space 1}    1.67{col 52}{space 3}0.097{col 60}{space 4}-.0502052{col 73}{space 3} .5927719
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .3970374{col 32}{space 2} .0996787{col 43}{space 1}    3.98{col 52}{space 3}0.000{col 60}{space 4} .1993481{col 73}{space 3} .5947266
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2} .2220671{col 32}{space 2} .0732361{col 43}{space 1}    3.03{col 52}{space 3}0.003{col 60}{space 4} .0768206{col 73}{space 3} .3673135
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0951149{col 32}{space 2} .0731131{col 43}{space 1}    1.30{col 52}{space 3}0.196{col 60}{space 4}-.0498878{col 73}{space 3} .2401175
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0344926{col 32}{space 2} .0732974{col 43}{space 1}    0.47{col 52}{space 3}0.639{col 60}{space 4}-.1108755{col 73}{space 3} .1798608
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} -.047744{col 32}{space 2} .0881326{col 43}{space 1}   -0.54{col 52}{space 3}0.589{col 60}{space 4}-.2225342{col 73}{space 3} .1270461
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .1426599{col 32}{space 2} .0908269{col 43}{space 1}    1.57{col 52}{space 3}0.119{col 60}{space 4}-.0374738{col 73}{space 3} .3227936
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0029863{col 32}{space 2} .0053427{col 43}{space 1}    0.56{col 52}{space 3}0.577{col 60}{space 4}-.0076096{col 73}{space 3} .0135823
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0034031{col 32}{space 2} .0055144{col 43}{space 1}    0.62{col 52}{space 3}0.539{col 60}{space 4}-.0075335{col 73}{space 3} .0143397
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .5172733{col 32}{space 2} .3224825{col 43}{space 1}    1.60{col 52}{space 3}0.112{col 60}{space 4}-.1222946{col 73}{space 3} 1.156841
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.1806238{col 32}{space 2} .3163985{col 43}{space 1}   -0.57{col 52}{space 3}0.569{col 60}{space 4}-.8081255{col 73}{space 3}  .446878
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2
{col 23}pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1
{col 23}longshort_spread_2 logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 13,   103) = {res}   22.95
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 11,   103) = {res}    9.36
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=10
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 13,   103) = {res}  187.29
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0586060405{txt}{col 55}Centered R2   = {res}  0.8891
{txt}Total (uncentered) SS   = {res} .0590151024{txt}{col 55}Uncentered R2 = {res}  0.8899
{txt}Residual SS             = {res} .0064973536{txt}{col 55}Root MSE      = {res} .007942

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          pi_hat_1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .2396719{col 32}{space 2} .1053486{col 43}{space 1}    2.28{col 52}{space 3}0.025{col 60}{space 4} .0307378{col 73}{space 3} .4486061
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .2880778{col 32}{space 2} .0987332{col 43}{space 1}    2.92{col 52}{space 3}0.004{col 60}{space 4} .0922638{col 73}{space 3} .4838919
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2}  .171336{col 32}{space 2} .0554821{col 43}{space 1}    3.09{col 52}{space 3}0.003{col 60}{space 4} .0613002{col 73}{space 3} .2813717
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2}-.0038152{col 32}{space 2} .0407059{col 43}{space 1}   -0.09{col 52}{space 3}0.926{col 60}{space 4}-.0845458{col 73}{space 3} .0769154
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2} .0333549{col 32}{space 2} .0220538{col 43}{space 1}    1.51{col 52}{space 3}0.133{col 60}{space 4}-.0103836{col 73}{space 3} .0770935
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0346413{col 32}{space 2} .0312947{col 43}{space 1}    1.11{col 52}{space 3}0.271{col 60}{space 4}-.0274244{col 73}{space 3}  .096707
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0374439{col 32}{space 2} .0283071{col 43}{space 1}    1.32{col 52}{space 3}0.189{col 60}{space 4}-.0186966{col 73}{space 3} .0935843
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1699955{col 32}{space 2} .0346243{col 43}{space 1}    4.91{col 52}{space 3}0.000{col 60}{space 4} .1013262{col 73}{space 3} .2386647
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0629171{col 32}{space 2} .0353823{col 43}{space 1}    1.78{col 52}{space 3}0.078{col 60}{space 4}-.0072554{col 73}{space 3} .1330897
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2}-.0010354{col 32}{space 2}   .00173{col 43}{space 1}   -0.60{col 52}{space 3}0.551{col 60}{space 4}-.0044664{col 73}{space 3} .0023956
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0017701{col 32}{space 2} .0015918{col 43}{space 1}    1.11{col 52}{space 3}0.269{col 60}{space 4}-.0013868{col 73}{space 3}  .004927
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2}-.1073642{col 32}{space 2} .1292674{col 43}{space 1}   -0.83{col 52}{space 3}0.408{col 60}{space 4}-.3637356{col 73}{space 3} .1490073
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} .1124605{col 32}{space 2} .1411266{col 43}{space 1}    0.80{col 52}{space 3}0.427{col 60}{space 4}-.1674308{col 73}{space 3} .3923517
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2
{col 23}pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1
{col 23}longshort_spread_2 logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 13,   103) = {res}  187.29
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 11,   103) = {res}    6.43
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=10
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F( 13,   103) = {res}   41.80
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0579688024{txt}{col 55}Centered R2   = {res}  0.8406
{txt}Total (uncentered) SS   = {res} .0582406245{txt}{col 55}Uncentered R2 = {res}  0.8414
{txt}Residual SS             = {res} .0092388883{txt}{col 55}Root MSE      = {res} .009471

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .2865209{col 32}{space 2} .1126321{col 43}{space 1}    2.54{col 52}{space 3}0.012{col 60}{space 4} .0631418{col 73}{space 3} .5099001
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .4740598{col 32}{space 2} .0856271{col 43}{space 1}    5.54{col 52}{space 3}0.000{col 60}{space 4} .3042386{col 73}{space 3}  .643881
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2}-.0103264{col 32}{space 2} .0811798{col 43}{space 1}   -0.13{col 52}{space 3}0.899{col 60}{space 4}-.1713273{col 73}{space 3} .1506746
{txt}{space 6}ROLC_h2fix_1 {c |}{col 20}{res}{space 2} .0595564{col 32}{space 2} .0370913{col 43}{space 1}    1.61{col 52}{space 3}0.111{col 60}{space 4}-.0140054{col 73}{space 3} .1331182
{txt}{space 6}ROLC_h2fix_2 {c |}{col 20}{res}{space 2} .0098544{col 32}{space 2}  .033112{col 43}{space 1}    0.30{col 52}{space 3}0.767{col 60}{space 4}-.0558154{col 73}{space 3} .0755242
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0676155{col 32}{space 2} .0342507{col 43}{space 1}    1.97{col 52}{space 3}0.051{col 60}{space 4}-.0003127{col 73}{space 3} .1355436
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2}  .027754{col 32}{space 2} .0265853{col 43}{space 1}    1.04{col 52}{space 3}0.299{col 60}{space 4}-.0249717{col 73}{space 3} .0804796
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1069439{col 32}{space 2} .0380949{col 43}{space 1}    2.81{col 52}{space 3}0.006{col 60}{space 4} .0313918{col 73}{space 3} .1824961
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0910343{col 32}{space 2} .0638675{col 43}{space 1}    1.43{col 52}{space 3}0.157{col 60}{space 4}-.0356318{col 73}{space 3} .2177004
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0012156{col 32}{space 2} .0031768{col 43}{space 1}    0.38{col 52}{space 3}0.703{col 60}{space 4}-.0050848{col 73}{space 3}  .007516
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0013033{col 32}{space 2} .0026586{col 43}{space 1}    0.49{col 52}{space 3}0.625{col 60}{space 4}-.0039694{col 73}{space 3}  .006576
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .0579497{col 32}{space 2} .1803376{col 43}{space 1}    0.32{col 52}{space 3}0.749{col 60}{space 4}-.2997075{col 73}{space 3} .4156069
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} .0516914{col 32}{space 2} .1722087{col 43}{space 1}    0.30{col 52}{space 3}0.765{col 60}{space 4}-.2898439{col 73}{space 3} .3932267
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_h2fix_1 ROLC_h2fix_2
{col 23}pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1
{col 23}longshort_spread_2 logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 13,   103) = {res}   41.80
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 11,   103) = {res}    3.25
{txt}  Prob > F      = {res}  0.0008



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 13{txt},{res}   103{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 11{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 11{txt},{res}   103{txt})
{res}ROLC_h2fix  {col 14}{txt}|{col 18}{res}   22.95{col 28}  0.0000{col 37}{txt}|{col 42}{res}  115.90{col 51}  0.0000{col 60}{txt}|{col 65}{res}    9.36
pi_hat_1    {col 14}{txt}|{col 18}{res}  187.29{col 28}  0.0000{col 37}{txt}|{col 42}{res}   79.71{col 51}  0.0000{col 60}{txt}|{col 65}{res}    6.43
pi_hat_F1   {col 14}{txt}|{col 18}{res}   41.80{col 28}  0.0000{col 37}{txt}|{col 42}{res}   40.21{col 51}  0.0000{col 60}{txt}|{col 65}{res}    3.25

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.10
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.51
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.56
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.80
{txt}{col 36}10% maximal IV size{res}{col 67} 40.90
{txt}{col 36}15% maximal IV size{res}{col 67} 22.06
{txt}{col 36}20% maximal IV size{res}{col 67} 15.56
{txt}{col 36}25% maximal IV size{res}{col 67} 12.23
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}11{txt})={res}8.21   {col 61}{txt}P-val={res}0.6947

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    0.84
Kleibergen-Paap Wald rk F statistic{col 65}    1.73

{txt}Stock-Yogo weak ID test critical values for K1=3 and L1=13:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 18.17
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 10.14
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  5.92
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.41
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}13{txt},{res}103{txt})={col 49}{res}  98.72{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}13{txt})={col 49}{res}1445.37{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}13{txt})={col 49}{res}   7.75{col 61}{txt}P-val={res}0.8592

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       116
{txt}Number of regressors                 K  = {res}         3
{txt}Number of endogenous regressors      K1 = {res}         3
{txt}Number of instruments                L  = {res}        13
{txt}Number of excluded instruments       L1 = {res}        13

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=10
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     116
{txt}{col 55}F(  3,   113) = {res} 1283.77
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0581346117{txt}{col 55}Centered R2   = {res}  0.8195
{txt}Total (uncentered) SS   = {res} .0584658598{txt}{col 55}Uncentered R2 = {res}  0.8205
{txt}Residual SS             = {res} .0104942563{txt}{col 55}Root MSE      = {res} .009511

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}ROLC_h2fix {c |}{col 14}{res}{space 2} .0540934{col 26}{space 2} .0325587{col 37}{space 1}    1.66{col 46}{space 3}0.097{col 54}{space 4}-.0097205{col 67}{space 3} .1179074
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .7969999{col 26}{space 2} .1365986{col 37}{space 1}    5.83{col 46}{space 3}0.000{col 54}{space 4} .5292716{col 67}{space 3} 1.064728
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .1811955{col 26}{space 2} .1461421{col 37}{space 1}    1.24{col 46}{space 3}0.215{col 54}{space 4}-.1052376{col 67}{space 3} .4676287
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. generate  delta_pi_hat_F1=pi_hat-pi_hat_F1
{txt}(446 missing values generated)

{com}. 
. generate  delta_pi_hat_1=pi_hat_1-pi_hat_F1
{txt}(447 missing values generated)

{com}. 
. ivregress gmm   delta_pi_hat_F1 ( RULC = pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 RULC_3 RULC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}1{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 18    {col 56}Root MSE{col 70}= {res}  .0104

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}delta_pi_~F1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}RULC {c |}{col 14}{res}{space 2} .0244362{col 26}{space 2}  .013929{col 37}{space 1}    1.75{col 46}{space 3}0.079{col 54}{space 4}-.0028642{col 67}{space 3} .0517365
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}RULC{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 RULC_3 RULC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 14 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}23{txt}) ={res} 6.25238{txt} (p = {res}0.9998{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[1,1]
           RULC
RULC {res} .00019402
{reset}
{com}. 
. ivregress gmm   delta_pi_hat_F1 ( ROLC = pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}1{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 8     {col 56}Root MSE{col 70}= {res} .01029

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}delta_pi_~F1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}ROLC {c |}{col 14}{res}{space 2}-.0334591{col 26}{space 2} .0165791{col 37}{space 1}   -2.02{col 46}{space 3}0.044{col 54}{space 4}-.0659535{col 67}{space 3}-.0009647
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 7 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}23{txt}) ={res} 9.44119{txt} (p = {res}0.9942{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[1,1]
           ROLC
ROLC {res} .00027487
{reset}
{com}. 
. ivregress gmm   delta_pi_hat_F1 ( RULC = pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}1{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 20    {col 56}Root MSE{col 70}= {res} .01041

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}delta_pi_~F1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}RULC {c |}{col 14}{res}{space 2} .0321978{col 26}{space 2} .0177429{col 37}{space 1}    1.81{col 46}{space 3}0.070{col 54}{space 4}-.0025777{col 67}{space 3} .0669733
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}RULC{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 20 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}13{txt}) ={res} 5.14919{txt} (p = {res}0.9718{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[1,1]
           RULC
RULC {res} .00031481
{reset}
{com}. 
. ivregress gmm   delta_pi_hat_F1 ( ROLC  = pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}1{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 5     {col 56}Root MSE{col 70}= {res} .01032

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}delta_pi_~F1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}ROLC {c |}{col 14}{res}{space 2}-.0214081{col 26}{space 2} .0456487{col 37}{space 1}   -0.47{col 46}{space 3}0.639{col 54}{space 4} -.110878{col 67}{space 3} .0680618
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 0 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}13{txt}) ={res} 8.95536{txt} (p = {res}0.7763{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[1,1]
           ROLC
ROLC {res} .00208381
{reset}
{com}. 
. ivregress gmm   delta_pi_hat_F1 ( RULC  delta_pi_hat_1=  pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 RULC_3 RULC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 20    {col 56}Root MSE{col 70}= {res}  .0089

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}      HAC
{col 1}delta_pi_ha~F1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}RULC {c |}{col 16}{res}{space 2} .0023433{col 28}{space 2} .0064248{col 39}{space 1}    0.36{col 48}{space 3}0.715{col 56}{space 4} -.010249{col 69}{space 3} .0149357
{txt}delta_pi_hat_1 {c |}{col 16}{res}{space 2} .5482622{col 28}{space 2} .0364567{col 39}{space 1}   15.04{col 48}{space 3}0.000{col 56}{space 4} .4768084{col 69}{space 3} .6197159
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 20}Instrumented:{space 2}RULC delta_pi_hat_1{p_end}
{p 0 15 20}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 RULC_3 RULC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 20 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}21{txt}) ={res} 5.88936{txt} (p = {res}0.9995{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
                      RULC  delta_pi_~_1
        RULC {res}    .00004128
{txt}delta_pi_~_1 {res}   -.00005955     .00132909
{reset}
{com}. 
. ivregress gmm   delta_pi_hat_F1 ( ROLC  delta_pi_hat_1=  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 20    {col 56}Root MSE{col 70}= {res} .00902

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}      HAC
{col 1}delta_pi_ha~F1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}ROLC {c |}{col 16}{res}{space 2} .0187835{col 28}{space 2} .0098743{col 39}{space 1}    1.90{col 48}{space 3}0.057{col 56}{space 4}-.0005698{col 69}{space 3} .0381369
{txt}delta_pi_hat_1 {c |}{col 16}{res}{space 2} .6343617{col 28}{space 2} .0536622{col 39}{space 1}   11.82{col 48}{space 3}0.000{col 56}{space 4} .5291856{col 69}{space 3} .7395377
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 20}Instrumented:{space 2}ROLC delta_pi_hat_1{p_end}
{p 0 15 20}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 20 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}21{txt}) ={res} 6.07452{txt} (p = {res}0.9994{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
                      ROLC  delta_pi_~_1
        ROLC {res}     .0000975
{txt}delta_pi_~_1 {res}     .0003911     .00287963
{reset}
{com}. 
. ivregress gmm   delta_pi_hat_F1 ( RULC  delta_pi_hat_1=  pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 20    {col 56}Root MSE{col 70}= {res} .00894

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}      HAC
{col 1}delta_pi_ha~F1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}RULC {c |}{col 16}{res}{space 2}   .00556{col 28}{space 2}  .008028{col 39}{space 1}    0.69{col 48}{space 3}0.489{col 56}{space 4}-.0101747{col 69}{space 3} .0212947
{txt}delta_pi_hat_1 {c |}{col 16}{res}{space 2} .5877765{col 28}{space 2} .0482467{col 39}{space 1}   12.18{col 48}{space 3}0.000{col 56}{space 4} .4932146{col 69}{space 3} .6823384
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 20}Instrumented:{space 2}RULC delta_pi_hat_1{p_end}
{p 0 15 20}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 RULC_1 RULC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 20 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}11{txt}) ={res} 5.64904{txt} (p = {res}0.8957{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
                      RULC  delta_pi_~_1
        RULC {res}    .00006445
{txt}delta_pi_~_1 {res}    -.0001237     .00232775
{reset}
{com}. 
. ivregress gmm   delta_pi_hat_F1 ( ROLC  delta_pi_hat_1=  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    116
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 20    {col 56}Root MSE{col 70}= {res} .00927

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}      HAC
{col 1}delta_pi_ha~F1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}ROLC {c |}{col 16}{res}{space 2} .0364205{col 28}{space 2} .0167146{col 39}{space 1}    2.18{col 48}{space 3}0.029{col 56}{space 4} .0036604{col 69}{space 3} .0691805
{txt}delta_pi_hat_1 {c |}{col 16}{res}{space 2} .7325075{col 28}{space 2} .0788276{col 39}{space 1}    9.29{col 48}{space 3}0.000{col 56}{space 4} .5780082{col 69}{space 3} .8870069
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 20}Instrumented:{space 2}ROLC delta_pi_hat_1{p_end}
{p 0 15 20}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 20 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}11{txt}) ={res}  5.8095{txt} (p = {res}0.8858{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
                      ROLC  delta_pi_~_1
        ROLC {res}    .00027938
{txt}delta_pi_~_1 {res}    .00109269      .0062138
{reset}
{com}. 
. sum ROLC, d

                            {txt}ROLC
{hline 61}
      Percentiles      Smallest
 1%    {res}-.0709876      -.0710263
{txt} 5%    {res}-.0455346      -.0709876
{txt}10%    {res}-.0375666      -.0661644       {txt}Obs         {res}        122
{txt}25%    {res} -.025309       -.065649       {txt}Sum of Wgt. {res}        122

{txt}50%    {res} .0031868                      {txt}Mean          {res}-1.03e-07
                        {txt}Largest       Std. Dev.     {res} .0303839
{txt}75%    {res}  .023623       .0513244
{txt}90%    {res} .0385347        .051682       {txt}Variance      {res} .0009232
{txt}95%    {res} .0459672       .0538331       {txt}Skewness      {res}-.1677435
{txt}99%    {res} .0538331       .0632563       {txt}Kurtosis      {res} 2.264126
{txt}
{com}. 
. g ROLC_out= ROLC if ROLC>=r(p5) & ROLC<=r(p95)
{txt}(594 missing values generated)

{com}. 
. ivregress gmm   pi_hat ( ROLC_out  pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    104
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 14    {col 56}Root MSE{col 70}= {res}  .0105

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2}-.0208494{col 26}{space 2} .0161276{col 37}{space 1}   -1.29{col 46}{space 3}0.196{col 54}{space 4}-.0524589{col 67}{space 3}   .01076
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .9853309{col 26}{space 2} .0136914{col 37}{space 1}   71.97{col 46}{space 3}0.000{col 54}{space 4} .9584963{col 67}{space 3} 1.012166
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_out pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 15 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}22{txt}) ={res} 7.40253{txt} (p = {res}0.9984{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
            ROLC_out  pi_hat_F1
 ROLC_out {res}  .0002601
{txt}pi_hat_F1 {res} .00002345  .00018745
{reset}
{com}. 
. ivreg2 pi_hat ( ROLC_out  pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238,  noconstant robust gmm2s nofooter bw(15) first ffirst
{res}{txt}Warning: time variable {res}date{txt} has {res}8{txt} gap(s) in relevant range
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_out:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=15
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 24,    80) = {res}   71.59
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0674280706{txt}{col 55}Centered R2   = {res}  0.6172
{txt}Total (uncentered) SS   = {res} .0674445911{txt}{col 55}Uncentered R2 = {res}  0.6173
{txt}Residual SS             = {res} .0258142399{txt}{col 55}Root MSE      = {res}  .01796

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          ROLC_out{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2}-.0373826{col 32}{space 2} .2334542{col 43}{space 1}   -0.16{col 52}{space 3}0.873{col 60}{space 4}-.5019713{col 73}{space 3}  .427206
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}-.3183867{col 32}{space 2}  .348692{col 43}{space 1}   -0.91{col 52}{space 3}0.364{col 60}{space 4}-1.012306{col 73}{space 3} .3755324
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .0839386{col 32}{space 2} .1288925{col 43}{space 1}    0.65{col 52}{space 3}0.517{col 60}{space 4}-.1725657{col 73}{space 3} .3404429
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .2021987{col 32}{space 2} .1752497{col 43}{space 1}    1.15{col 52}{space 3}0.252{col 60}{space 4}-.1465593{col 73}{space 3} .5509568
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .2222677{col 32}{space 2} .0821881{col 43}{space 1}    2.70{col 52}{space 3}0.008{col 60}{space 4} .0587083{col 73}{space 3} .3858272
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2} .1554602{col 32}{space 2} .0708389{col 43}{space 1}    2.19{col 52}{space 3}0.031{col 60}{space 4} .0144864{col 73}{space 3} .2964341
{txt}{space 12}ROLC_3 {c |}{col 20}{res}{space 2} .2184846{col 32}{space 2} .0463283{col 43}{space 1}    4.72{col 52}{space 3}0.000{col 60}{space 4} .1262883{col 73}{space 3} .3106809
{txt}{space 12}ROLC_4 {c |}{col 20}{res}{space 2} .1343839{col 32}{space 2} .0792429{col 43}{space 1}    1.70{col 52}{space 3}0.094{col 60}{space 4}-.0233144{col 73}{space 3} .2920822
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0525718{col 32}{space 2} .1150226{col 43}{space 1}    0.46{col 52}{space 3}0.649{col 60}{space 4}-.1763305{col 73}{space 3}  .281474
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0976636{col 32}{space 2} .0609235{col 43}{space 1}    1.60{col 52}{space 3}0.113{col 60}{space 4}-.0235781{col 73}{space 3} .2189053
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2} .0268038{col 32}{space 2}  .064952{col 43}{space 1}    0.41{col 52}{space 3}0.681{col 60}{space 4}-.1024547{col 73}{space 3} .1560623
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0873852{col 32}{space 2} .0645485{col 43}{space 1}    1.35{col 52}{space 3}0.180{col 60}{space 4}-.0410704{col 73}{space 3} .2158407
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2}-.0877546{col 32}{space 2} .1216429{col 43}{space 1}   -0.72{col 52}{space 3}0.473{col 60}{space 4}-.3298317{col 73}{space 3} .1543225
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0826225{col 32}{space 2} .1054436{col 43}{space 1}    0.78{col 52}{space 3}0.436{col 60}{space 4}-.1272169{col 73}{space 3} .2924619
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} .0278057{col 32}{space 2} .1212042{col 43}{space 1}    0.23{col 52}{space 3}0.819{col 60}{space 4}-.2133984{col 73}{space 3} .2690098
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2} .0998307{col 32}{space 2} .1029066{col 43}{space 1}    0.97{col 52}{space 3}0.335{col 60}{space 4}  -.10496{col 73}{space 3} .3046213
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2}-.0025785{col 32}{space 2} .0034432{col 43}{space 1}   -0.75{col 52}{space 3}0.456{col 60}{space 4}-.0094306{col 73}{space 3} .0042736
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0092168{col 32}{space 2} .0054324{col 43}{space 1}    1.70{col 52}{space 3}0.094{col 60}{space 4}-.0015941{col 73}{space 3} .0200277
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2}-.0063852{col 32}{space 2} .0050729{col 43}{space 1}   -1.26{col 52}{space 3}0.212{col 60}{space 4}-.0164806{col 73}{space 3} .0037103
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0021173{col 32}{space 2} .0036934{col 43}{space 1}    0.57{col 52}{space 3}0.568{col 60}{space 4}-.0052328{col 73}{space 3} .0094674
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .3333644{col 32}{space 2} .2059848{col 43}{space 1}    1.62{col 52}{space 3}0.110{col 60}{space 4}-.0765583{col 73}{space 3} .7432871
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.0683267{col 32}{space 2} .2975654{col 43}{space 1}   -0.23{col 52}{space 3}0.819{col 60}{space 4}-.6605007{col 73}{space 3} .5238474
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2}-.0038047{col 32}{space 2} .2697521{col 43}{space 1}   -0.01{col 52}{space 3}0.989{col 60}{space 4}-.5406284{col 73}{space 3}  .533019
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.1539257{col 32}{space 2} .2180526{col 43}{space 1}   -0.71{col 52}{space 3}0.482{col 60}{space 4}-.5878641{col 73}{space 3} .2800127
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3
{col 23}ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3
{col 23}pi_pc_4 longshort_spread_1 longshort_spread_2
{col 23}longshort_spread_3 longshort_spread_4 logy_detrended_1
{col 23}logy_detrended_2 logy_detrended_3 logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 24,    80) = {res}   71.59
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 23,    80) = {res}   70.61
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=15
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 24,    80) = {res}  133.93
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0547661968{txt}{col 55}Centered R2   = {res}  0.8677
{txt}Total (uncentered) SS   = {res} .0548667361{txt}{col 55}Uncentered R2 = {res}  0.8679
{txt}Residual SS             = {res} .0072457143{txt}{col 55}Root MSE      = {res} .009517

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2} .4095193{col 32}{space 2} .0928297{col 43}{space 1}    4.41{col 52}{space 3}0.000{col 60}{space 4} .2247824{col 73}{space 3} .5942562
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .3181468{col 32}{space 2}  .128266{col 43}{space 1}    2.48{col 52}{space 3}0.015{col 60}{space 4} .0628893{col 73}{space 3} .5734043
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .3058354{col 32}{space 2} .1075123{col 43}{space 1}    2.84{col 52}{space 3}0.006{col 60}{space 4} .0918791{col 73}{space 3} .5197918
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2}-.0348476{col 32}{space 2} .1281858{col 43}{space 1}   -0.27{col 52}{space 3}0.786{col 60}{space 4}-.2899454{col 73}{space 3} .2202503
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .0610204{col 32}{space 2} .0541595{col 43}{space 1}    1.13{col 52}{space 3}0.263{col 60}{space 4}-.0467605{col 73}{space 3} .1688012
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2}-.0209759{col 32}{space 2} .0478685{col 43}{space 1}   -0.44{col 52}{space 3}0.662{col 60}{space 4}-.1162372{col 73}{space 3} .0742855
{txt}{space 12}ROLC_3 {c |}{col 20}{res}{space 2}-.0147646{col 32}{space 2} .0475216{col 43}{space 1}   -0.31{col 52}{space 3}0.757{col 60}{space 4}-.1093356{col 73}{space 3} .0798063
{txt}{space 12}ROLC_4 {c |}{col 20}{res}{space 2}-.0130992{col 32}{space 2}  .066921{col 43}{space 1}   -0.20{col 52}{space 3}0.845{col 60}{space 4}-.1462763{col 73}{space 3} .1200778
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0548393{col 32}{space 2} .0278342{col 43}{space 1}    1.97{col 52}{space 3}0.052{col 60}{space 4}-.0005526{col 73}{space 3} .1102311
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0246662{col 32}{space 2} .0405146{col 43}{space 1}    0.61{col 52}{space 3}0.544{col 60}{space 4}-.0559604{col 73}{space 3} .1052928
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2}-.0043114{col 32}{space 2} .0419725{col 43}{space 1}   -0.10{col 52}{space 3}0.918{col 60}{space 4}-.0878394{col 73}{space 3} .0792165
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0186074{col 32}{space 2} .0384612{col 43}{space 1}    0.48{col 52}{space 3}0.630{col 60}{space 4}-.0579328{col 73}{space 3} .0951476
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .0377592{col 32}{space 2} .0257661{col 43}{space 1}    1.47{col 52}{space 3}0.147{col 60}{space 4} -.013517{col 73}{space 3} .0890354
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0434549{col 32}{space 2}  .050628{col 43}{space 1}    0.86{col 52}{space 3}0.393{col 60}{space 4} -.057298{col 73}{space 3} .1442078
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} .0188629{col 32}{space 2} .0385855{col 43}{space 1}    0.49{col 52}{space 3}0.626{col 60}{space 4}-.0579248{col 73}{space 3} .0956505
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2}-.0235757{col 32}{space 2} .0421405{col 43}{space 1}   -0.56{col 52}{space 3}0.577{col 60}{space 4}-.1074379{col 73}{space 3} .0602865
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0040709{col 32}{space 2} .0043597{col 43}{space 1}    0.93{col 52}{space 3}0.353{col 60}{space 4}-.0046051{col 73}{space 3} .0127469
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2}-.0038834{col 32}{space 2} .0034809{col 43}{space 1}   -1.12{col 52}{space 3}0.268{col 60}{space 4}-.0108106{col 73}{space 3} .0030438
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2} .0007299{col 32}{space 2} .0024753{col 43}{space 1}    0.29{col 52}{space 3}0.769{col 60}{space 4} -.004196{col 73}{space 3} .0056559
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0018048{col 32}{space 2} .0019985{col 43}{space 1}    0.90{col 52}{space 3}0.369{col 60}{space 4}-.0021724{col 73}{space 3}  .005782
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .1447301{col 32}{space 2} .1340946{col 43}{space 1}    1.08{col 52}{space 3}0.284{col 60}{space 4}-.1221266{col 73}{space 3} .4115868
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.0154899{col 32}{space 2} .1596184{col 43}{space 1}   -0.10{col 52}{space 3}0.923{col 60}{space 4}-.3331405{col 73}{space 3} .3021608
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2} .0624283{col 32}{space 2} .1575099{col 43}{space 1}    0.40{col 52}{space 3}0.693{col 60}{space 4}-.2510264{col 73}{space 3} .3758829
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.0766467{col 32}{space 2} .1105742{col 43}{space 1}   -0.69{col 52}{space 3}0.490{col 60}{space 4}-.2966963{col 73}{space 3}  .143403
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3
{col 23}ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3
{col 23}pi_pc_4 longshort_spread_1 longshort_spread_2
{col 23}longshort_spread_3 longshort_spread_4 logy_detrended_1
{col 23}logy_detrended_2 logy_detrended_3 logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 24,    80) = {res}  133.93
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 23,    80) = {res}  136.00
{txt}  Prob > F      = {res}  0.0000



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 24{txt},{res}    80{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 23{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 23{txt},{res}    80{txt})
{res}ROLC_out    {col 14}{txt}|{col 18}{res}   71.59{col 28}  0.0000{col 37}{txt}|{col 42}{res} 2111.22{col 51}  0.0000{col 60}{txt}|{col 65}{res}   70.61
pi_hat_F1   {col 14}{txt}|{col 18}{res}  133.93{col 28}  0.0000{col 37}{txt}|{col 42}{res} 4066.38{col 51}  0.0000{col 60}{txt}|{col 65}{res}  136.00

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.41
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.41
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.22
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.41
{txt}{col 36}10% maximal IV size{res}{col 67} 69.46
{txt}{col 36}15% maximal IV size{res}{col 67} 36.37
{txt}{col 36}20% maximal IV size{res}{col 67} 25.10
{txt}{col 36}25% maximal IV size{res}{col 67} 19.41
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}23{txt})={res}8.23   {col 61}{txt}P-val={res}0.9980

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    5.11
Kleibergen-Paap Wald rk F statistic{col 65}   64.74

{txt}Stock-Yogo weak ID test critical values for K1=2 and L1=24:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 20.69
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.05
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.06
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.32
{txt}{col 36}10% maximal IV size{res}{col 67} 53.39
{txt}{col 36}15% maximal IV size{res}{col 67} 28.42
{txt}{col 36}20% maximal IV size{res}{col 67} 19.97
{txt}{col 36}25% maximal IV size{res}{col 67} 15.64
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}24{txt},{res}80{txt})={col 49}{res} 274.80{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}24{txt})={col 49}{res}8573.80{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}24{txt})={col 49}{res}   7.17{col 61}{txt}P-val={res}0.9996

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       104
{txt}Number of regressors                 K  = {res}         2
{txt}Number of endogenous regressors      K1 = {res}         2
{txt}Number of instruments                L  = {res}        24
{txt}Number of excluded instruments       L1 = {res}        24

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=15
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F(  2,   102) = {res} 2476.81
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0543417583{txt}{col 55}Centered R2   = {res}  0.7891
{txt}Total (uncentered) SS   = {res} .0544151079{txt}{col 55}Uncentered R2 = {res}  0.7893
{txt}Residual SS             = {res} .0114633104{txt}{col 55}Root MSE      = {res}   .0105

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2}-.0208494{col 26}{space 2}  .015524{col 37}{space 1}   -1.34{col 46}{space 3}0.179{col 54}{space 4}-.0512758{col 67}{space 3} .0095769
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .9853309{col 26}{space 2} .0143941{col 37}{space 1}   68.45{col 46}{space 3}0.000{col 54}{space 4}  .957119{col 67}{space 3} 1.013543
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ivregress gmm   pi_hat ( ROLC_out  pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    104
{txt}{col 1}{col 56}Wald chi2({res}2{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 13    {col 56}Root MSE{col 70}= {res} .01056

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2}-.0103375{col 26}{space 2} .0215845{col 37}{space 1}   -0.48{col 46}{space 3}0.632{col 54}{space 4}-.0526423{col 67}{space 3} .0319673
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .9930178{col 26}{space 2} .0191771{col 37}{space 1}   51.78{col 46}{space 3}0.000{col 54}{space 4} .9554314{col 67}{space 3} 1.030604
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_out pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 13 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}12{txt}) ={res} 6.52131{txt} (p = {res}0.8876{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[2,2]
            ROLC_out  pi_hat_F1
 ROLC_out {res} .00046589
{txt}pi_hat_F1 {res} .00004107  .00036776
{reset}
{com}. 
. ivreg2  pi_hat ( ROLC_out  pi_hat_F1= pi_hat_1  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant robust gmm2s nofooter bw(14) first ffirst
{res}{txt}Warning: time variable {res}date{txt} has {res}8{txt} gap(s) in relevant range
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_out:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=14
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 14,    90) = {res}   74.59
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0674280706{txt}{col 55}Centered R2   = {res}  0.5635
{txt}Total (uncentered) SS   = {res} .0674445911{txt}{col 55}Uncentered R2 = {res}  0.5636
{txt}Residual SS             = {res} .0294351463{txt}{col 55}Root MSE      = {res}  .01808

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          ROLC_out{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2} .0056951{col 32}{space 2} .2910238{col 43}{space 1}    0.02{col 52}{space 3}0.984{col 60}{space 4}-.5724744{col 73}{space 3} .5838645
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}-.0778465{col 32}{space 2} .2653358{col 43}{space 1}   -0.29{col 52}{space 3}0.770{col 60}{space 4}-.6049823{col 73}{space 3} .4492893
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .1194611{col 32}{space 2}  .093505{col 43}{space 1}    1.28{col 52}{space 3}0.205{col 60}{space 4}-.0663029{col 73}{space 3} .3052251
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1388716{col 32}{space 2} .1550613{col 43}{space 1}    0.90{col 52}{space 3}0.373{col 60}{space 4}-.1691848{col 73}{space 3}  .446928
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .3340754{col 32}{space 2} .0715272{col 43}{space 1}    4.67{col 52}{space 3}0.000{col 60}{space 4} .1919742{col 73}{space 3} .4761767
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2} .2608076{col 32}{space 2} .0742494{col 43}{space 1}    3.51{col 52}{space 3}0.001{col 60}{space 4} .1132981{col 73}{space 3}  .408317
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2}  .036865{col 32}{space 2} .0937947{col 43}{space 1}    0.39{col 52}{space 3}0.695{col 60}{space 4}-.1494745{col 73}{space 3} .2232046
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0321169{col 32}{space 2}  .053702{col 43}{space 1}    0.60{col 52}{space 3}0.551{col 60}{space 4}-.0745715{col 73}{space 3} .1388053
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2}-.0926593{col 32}{space 2} .0939689{col 43}{space 1}   -0.99{col 52}{space 3}0.327{col 60}{space 4}-.2793449{col 73}{space 3} .0940262
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0509437{col 32}{space 2}  .094668{col 43}{space 1}    0.54{col 52}{space 3}0.592{col 60}{space 4}-.1371307{col 73}{space 3} .2390182
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0016798{col 32}{space 2} .0035764{col 43}{space 1}    0.47{col 52}{space 3}0.640{col 60}{space 4}-.0054254{col 73}{space 3} .0087849
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0013787{col 32}{space 2} .0040822{col 43}{space 1}    0.34{col 52}{space 3}0.736{col 60}{space 4}-.0067312{col 73}{space 3} .0094886
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2}  .444421{col 32}{space 2} .2106168{col 43}{space 1}    2.11{col 52}{space 3}0.038{col 60}{space 4}  .025994{col 73}{space 3} .8628481
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} -.176086{col 32}{space 2}  .243785{col 43}{space 1}   -0.72{col 52}{space 3}0.472{col 60}{space 4}-.6604074{col 73}{space 3} .3082355
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1
{col 23}pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1
{col 23}longshort_spread_2 logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 14,    90) = {res}   74.59
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 13,    90) = {res}   75.12
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=14
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 14,    90) = {res}   58.51
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0547661968{txt}{col 55}Centered R2   = {res}  0.8594
{txt}Total (uncentered) SS   = {res} .0548667361{txt}{col 55}Uncentered R2 = {res}  0.8596
{txt}Residual SS             = {res} .0077027741{txt}{col 55}Root MSE      = {res} .009251

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_1 {c |}{col 20}{res}{space 2} .4110542{col 32}{space 2} .0862603{col 43}{space 1}    4.77{col 52}{space 3}0.000{col 60}{space 4} .2396831{col 73}{space 3} .5824253
{txt}{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .2941614{col 32}{space 2} .1029347{col 43}{space 1}    2.86{col 52}{space 3}0.005{col 60}{space 4} .0896637{col 73}{space 3} .4986591
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .3083371{col 32}{space 2} .0723405{col 43}{space 1}    4.26{col 52}{space 3}0.000{col 60}{space 4} .1646202{col 73}{space 3}  .452054
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2}-.0485585{col 32}{space 2} .0843787{col 43}{space 1}   -0.58{col 52}{space 3}0.566{col 60}{space 4}-.2161914{col 73}{space 3} .1190745
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .0468159{col 32}{space 2} .0336937{col 43}{space 1}    1.39{col 52}{space 3}0.168{col 60}{space 4}-.0201225{col 73}{space 3} .1137543
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2}-.0200113{col 32}{space 2} .0507712{col 43}{space 1}   -0.39{col 52}{space 3}0.694{col 60}{space 4}-.1208771{col 73}{space 3} .0808546
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0409999{col 32}{space 2}  .030439{col 43}{space 1}    1.35{col 52}{space 3}0.181{col 60}{space 4}-.0194725{col 73}{space 3} .1014723
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0188321{col 32}{space 2} .0307906{col 43}{space 1}    0.61{col 52}{space 3}0.542{col 60}{space 4}-.0423389{col 73}{space 3} .0800031
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .0230088{col 32}{space 2} .0302257{col 43}{space 1}    0.76{col 52}{space 3}0.449{col 60}{space 4}-.0370399{col 73}{space 3} .0830575
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0502248{col 32}{space 2} .0535913{col 43}{space 1}    0.94{col 52}{space 3}0.351{col 60}{space 4}-.0562436{col 73}{space 3} .1566932
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0032985{col 32}{space 2} .0040856{col 43}{space 1}    0.81{col 52}{space 3}0.422{col 60}{space 4}-.0048182{col 73}{space 3} .0114152
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2}-.0011786{col 32}{space 2}  .003604{col 43}{space 1}   -0.33{col 52}{space 3}0.744{col 60}{space 4}-.0083385{col 73}{space 3} .0059813
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .1812869{col 32}{space 2} .1194548{col 43}{space 1}    1.52{col 52}{space 3}0.133{col 60}{space 4}-.0560309{col 73}{space 3} .4186047
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.0494342{col 32}{space 2} .1138474{col 43}{space 1}   -0.43{col 52}{space 3}0.665{col 60}{space 4}-.2756119{col 73}{space 3} .1767435
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_1 pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1
{col 23}pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1
{col 23}longshort_spread_2 logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 14,    90) = {res}   58.51
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 13,    90) = {res}   60.90
{txt}  Prob > F      = {res}  0.0000



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 14{txt},{res}    90{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 13{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 13{txt},{res}    90{txt})
{res}ROLC_out    {col 14}{txt}|{col 18}{res}   74.59{col 28}  0.0000{col 37}{txt}|{col 42}{res} 1128.41{col 51}  0.0000{col 60}{txt}|{col 65}{res}   75.12
pi_hat_F1   {col 14}{txt}|{col 18}{res}   58.51{col 28}  0.0000{col 37}{txt}|{col 42}{res}  914.80{col 51}  0.0000{col 60}{txt}|{col 65}{res}   60.90

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.18
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.52
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.49
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.71
{txt}{col 36}10% maximal IV size{res}{col 67} 45.64
{txt}{col 36}15% maximal IV size{res}{col 67} 24.42
{txt}{col 36}20% maximal IV size{res}{col 67} 17.14
{txt}{col 36}25% maximal IV size{res}{col 67} 13.41
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}13{txt})={res}8.39   {col 61}{txt}P-val={res}0.8174

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    7.82
Kleibergen-Paap Wald rk F statistic{col 65}   61.98

{txt}Stock-Yogo weak ID test critical values for K1=2 and L1=14:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 19.83
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 10.89
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.20
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.53
{txt}{col 36}10% maximal IV size{res}{col 67} 36.36
{txt}{col 36}15% maximal IV size{res}{col 67} 19.72
{txt}{col 36}20% maximal IV size{res}{col 67} 14.05
{txt}{col 36}25% maximal IV size{res}{col 67} 11.13
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}14{txt},{res}90{txt})={col 49}{res} 192.86{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}14{txt})={col 49}{res}3120.08{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}14{txt})={col 49}{res}   6.25{col 61}{txt}P-val={res}0.9597

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       104
{txt}Number of regressors                 K  = {res}         2
{txt}Number of endogenous regressors      K1 = {res}         2
{txt}Number of instruments                L  = {res}        14
{txt}Number of excluded instruments       L1 = {res}        14

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=14
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F(  2,   102) = {res} 1334.57
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0543417583{txt}{col 55}Centered R2   = {res}  0.7866
{txt}Total (uncentered) SS   = {res} .0544151079{txt}{col 55}Uncentered R2 = {res}  0.7869
{txt}Residual SS             = {res} .0115969486{txt}{col 55}Root MSE      = {res}  .01056

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2}-.0103375{col 26}{space 2} .0209645{col 37}{space 1}   -0.49{col 46}{space 3}0.622{col 54}{space 4}-.0514271{col 67}{space 3} .0307521
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .9930178{col 26}{space 2} .0191406{col 37}{space 1}   51.88{col 46}{space 3}0.000{col 54}{space 4} .9555029{col 67}{space 3} 1.030533
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ivregress gmm   pi_hat ( ROLC_out pi_hat_1 pi_hat_F1=  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    104
{txt}{col 1}{col 56}Wald chi2({res}3{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 19    {col 56}Root MSE{col 70}= {res} .00907

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2} .0305493{col 26}{space 2} .0101872{col 37}{space 1}    3.00{col 46}{space 3}0.003{col 54}{space 4} .0105827{col 67}{space 3} .0505158
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .5893624{col 26}{space 2} .0523537{col 37}{space 1}   11.26{col 46}{space 3}0.000{col 54}{space 4} .4867511{col 67}{space 3} .6919737
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .4089333{col 26}{space 2}  .055133{col 37}{space 1}    7.42{col 46}{space 3}0.000{col 54}{space 4} .3008745{col 67}{space 3}  .516992
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_out pi_hat_1 pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4{p_end}
HAC VCE:{col 16}Bartlett kernel with 19 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}20{txt}) ={res} 6.19284{txt} (p = {res}0.9986{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[3,3]
             ROLC_out    pi_hat_1   pi_hat_F1
 ROLC_out {res}  .00010378
{txt} pi_hat_1 {res}  .00026969   .00274091
{txt}pi_hat_F1 {res}  -.0002734  -.00284885   .00303965
{reset}
{com}. 
. ivreg2 pi_hat ( ROLC_out pi_hat_1 pi_hat_F1=  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4 pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2  pi_pc_3 pi_pc_4 longshort_spread_1 longshort_spread_2 longshort_spread_3 longshort_spread_4 logy_detrended_1 logy_detrended_2 logy_detrended_3 logy_detrended_4) in 123/238,  noconstant robust gmm2s nofooter bw(20) first ffirst
{res}{txt}Warning: time variable {res}date{txt} has {res}8{txt} gap(s) in relevant range
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_out:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=20
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 23,    81) = {res}   98.78
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0674280706{txt}{col 55}Centered R2   = {res}  0.6170
{txt}Total (uncentered) SS   = {res} .0674445911{txt}{col 55}Uncentered R2 = {res}  0.6171
{txt}Residual SS             = {res} .0258217809{txt}{col 55}Root MSE      = {res}  .01785

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          ROLC_out{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}-.3255572{col 32}{space 2} .3325502{col 43}{space 1}   -0.98{col 52}{space 3}0.331{col 60}{space 4}-.9872278{col 73}{space 3} .3361134
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2}  .072544{col 32}{space 2}  .161244{col 43}{space 1}    0.45{col 52}{space 3}0.654{col 60}{space 4} -.248281{col 73}{space 3} .3933689
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1966702{col 32}{space 2} .1705428{col 43}{space 1}    1.15{col 52}{space 3}0.252{col 60}{space 4}-.1426565{col 73}{space 3} .5359969
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .2236285{col 32}{space 2} .0783302{col 43}{space 1}    2.85{col 52}{space 3}0.005{col 60}{space 4}  .067776{col 73}{space 3} .3794809
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2} .1535541{col 32}{space 2} .0632938{col 43}{space 1}    2.43{col 52}{space 3}0.017{col 60}{space 4} .0276194{col 73}{space 3} .2794888
{txt}{space 12}ROLC_3 {c |}{col 20}{res}{space 2} .2153158{col 32}{space 2}  .053672{col 43}{space 1}    4.01{col 52}{space 3}0.000{col 60}{space 4} .1085254{col 73}{space 3} .3221062
{txt}{space 12}ROLC_4 {c |}{col 20}{res}{space 2} .1369659{col 32}{space 2}  .073768{col 43}{space 1}    1.86{col 52}{space 3}0.067{col 60}{space 4}-.0098092{col 73}{space 3}  .283741
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2}  .050155{col 32}{space 2} .1071969{col 43}{space 1}    0.47{col 52}{space 3}0.641{col 60}{space 4}-.1631332{col 73}{space 3} .2634432
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0960304{col 32}{space 2} .0547664{col 43}{space 1}    1.75{col 52}{space 3}0.083{col 60}{space 4}-.0129375{col 73}{space 3} .2049984
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2} .0277141{col 32}{space 2} .0558633{col 43}{space 1}    0.50{col 52}{space 3}0.621{col 60}{space 4}-.0834363{col 73}{space 3} .1388645
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0869762{col 32}{space 2} .0596054{col 43}{space 1}    1.46{col 52}{space 3}0.148{col 60}{space 4}-.0316198{col 73}{space 3} .2055723
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2}-.0950981{col 32}{space 2} .1183308{col 43}{space 1}   -0.80{col 52}{space 3}0.424{col 60}{space 4}-.3305393{col 73}{space 3} .1403432
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0798346{col 32}{space 2}  .103296{col 43}{space 1}    0.77{col 52}{space 3}0.442{col 60}{space 4} -.125692{col 73}{space 3} .2853612
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} .0280852{col 32}{space 2} .1189654{col 43}{space 1}    0.24{col 52}{space 3}0.814{col 60}{space 4}-.2086187{col 73}{space 3} .2647891
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2} .0993102{col 32}{space 2} .0955895{col 43}{space 1}    1.04{col 52}{space 3}0.302{col 60}{space 4} -.090883{col 73}{space 3} .2895033
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2}-.0025085{col 32}{space 2} .0035737{col 43}{space 1}   -0.70{col 52}{space 3}0.485{col 60}{space 4}-.0096191{col 73}{space 3} .0046021
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0091175{col 32}{space 2} .0052992{col 43}{space 1}    1.72{col 52}{space 3}0.089{col 60}{space 4}-.0014262{col 73}{space 3} .0196613
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2}-.0063723{col 32}{space 2} .0044419{col 43}{space 1}   -1.43{col 52}{space 3}0.155{col 60}{space 4}-.0152103{col 73}{space 3} .0024658
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0020882{col 32}{space 2} .0033773{col 43}{space 1}    0.62{col 52}{space 3}0.538{col 60}{space 4}-.0046317{col 73}{space 3}  .008808
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .3377011{col 32}{space 2} .1937517{col 43}{space 1}    1.74{col 52}{space 3}0.085{col 60}{space 4} -.047804{col 73}{space 3} .7232061
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.0731495{col 32}{space 2} .2832917{col 43}{space 1}   -0.26{col 52}{space 3}0.797{col 60}{space 4}-.6368111{col 73}{space 3}  .490512
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2} .0003524{col 32}{space 2} .2254491{col 43}{space 1}    0.00{col 52}{space 3}0.999{col 60}{space 4}-.4482206{col 73}{space 3} .4489254
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.1576989{col 32}{space 2} .1980331{col 43}{space 1}   -0.80{col 52}{space 3}0.428{col 60}{space 4}-.5517228{col 73}{space 3} .2363249
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4
{col 23}pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3
{col 23}pi_pc_4 longshort_spread_1 longshort_spread_2
{col 23}longshort_spread_3 longshort_spread_4 logy_detrended_1
{col 23}logy_detrended_2 logy_detrended_3 logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 23,    81) = {res}   98.78
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 21,    81) = {res}   92.26
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=20
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 23,    81) = {res}  349.34
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0517944558{txt}{col 55}Centered R2   = {res}  0.8958
{txt}Total (uncentered) SS   = {res} .0518955603{txt}{col 55}Uncentered R2 = {res}  0.8960
{txt}Residual SS             = {res} .0053962665{txt}{col 55}Root MSE      = {res} .008162

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          pi_hat_1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .1918132{col 32}{space 2} .1021634{col 43}{space 1}    1.88{col 52}{space 3}0.064{col 60}{space 4}-.0114599{col 73}{space 3} .3950863
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .3048109{col 32}{space 2} .0730848{col 43}{space 1}    4.17{col 52}{space 3}0.000{col 60}{space 4} .1593952{col 73}{space 3} .4502267
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1478908{col 32}{space 2} .0550924{col 43}{space 1}    2.68{col 52}{space 3}0.009{col 60}{space 4} .0382742{col 73}{space 3} .2575074
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2}   -.0364{col 32}{space 2} .0484014{col 43}{space 1}   -0.75{col 52}{space 3}0.454{col 60}{space 4}-.1327035{col 73}{space 3} .0599036
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2} .0509904{col 32}{space 2}   .02916{col 43}{space 1}    1.75{col 52}{space 3}0.084{col 60}{space 4}-.0070288{col 73}{space 3} .1090097
{txt}{space 12}ROLC_3 {c |}{col 20}{res}{space 2} .0847674{col 32}{space 2} .0593157{col 43}{space 1}    1.43{col 52}{space 3}0.157{col 60}{space 4}-.0332523{col 73}{space 3}  .202787
{txt}{space 12}ROLC_4 {c |}{col 20}{res}{space 2}-.0690685{col 32}{space 2} .0512821{col 43}{space 1}   -1.35{col 52}{space 3}0.182{col 60}{space 4}-.1711038{col 73}{space 3} .0329668
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0646485{col 32}{space 2} .0235205{col 43}{space 1}    2.75{col 52}{space 3}0.007{col 60}{space 4} .0178501{col 73}{space 3}  .111447
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2}  .043687{col 32}{space 2} .0389206{col 43}{space 1}    1.12{col 52}{space 3}0.265{col 60}{space 4}-.0337528{col 73}{space 3} .1211268
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2}-.0243529{col 32}{space 2} .0250348{col 43}{space 1}   -0.97{col 52}{space 3}0.334{col 60}{space 4}-.0741643{col 73}{space 3} .0254584
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0109394{col 32}{space 2} .0170092{col 43}{space 1}    0.64{col 52}{space 3}0.522{col 60}{space 4}-.0229034{col 73}{space 3} .0447823
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1964411{col 32}{space 2} .0280822{col 43}{space 1}    7.00{col 52}{space 3}0.000{col 60}{space 4} .1405664{col 73}{space 3} .2523158
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0745769{col 32}{space 2} .0388644{col 43}{space 1}    1.92{col 52}{space 3}0.059{col 60}{space 4}-.0027511{col 73}{space 3} .1519048
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} -.007475{col 32}{space 2} .0214394{col 43}{space 1}   -0.35{col 52}{space 3}0.728{col 60}{space 4}-.0501326{col 73}{space 3} .0351826
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2} .0139246{col 32}{space 2} .0345407{col 43}{space 1}    0.40{col 52}{space 3}0.688{col 60}{space 4}-.0548007{col 73}{space 3} .0826498
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2}-.0018724{col 32}{space 2} .0020189{col 43}{space 1}   -0.93{col 52}{space 3}0.356{col 60}{space 4}-.0058895{col 73}{space 3} .0021446
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0026543{col 32}{space 2} .0031275{col 43}{space 1}    0.85{col 52}{space 3}0.399{col 60}{space 4}-.0035684{col 73}{space 3}  .008877
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2}-.0003445{col 32}{space 2} .0023042{col 43}{space 1}   -0.15{col 52}{space 3}0.882{col 60}{space 4}-.0049291{col 73}{space 3} .0042401
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0007787{col 32}{space 2} .0019162{col 43}{space 1}    0.41{col 52}{space 3}0.686{col 60}{space 4}-.0030339{col 73}{space 3} .0045914
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2}-.1160071{col 32}{space 2} .1712228{col 43}{space 1}   -0.68{col 52}{space 3}0.500{col 60}{space 4}-.4566868{col 73}{space 3} .2246725
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} .1290135{col 32}{space 2} .1825628{col 43}{space 1}    0.71{col 52}{space 3}0.482{col 60}{space 4}-.2342293{col 73}{space 3} .4922562
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2}-.1112048{col 32}{space 2}  .170066{col 43}{space 1}   -0.65{col 52}{space 3}0.515{col 60}{space 4}-.4495827{col 73}{space 3} .2271732
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2} .1009348{col 32}{space 2} .1380166{col 43}{space 1}    0.73{col 52}{space 3}0.467{col 60}{space 4} -.173675{col 73}{space 3} .3755446
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4
{col 23}pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3
{col 23}pi_pc_4 longshort_spread_1 longshort_spread_2
{col 23}longshort_spread_3 longshort_spread_4 logy_detrended_1
{col 23}logy_detrended_2 logy_detrended_3 logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 23,    81) = {res}  349.34
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 21,    81) = {res}   13.40
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=20
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 23,    81) = {res}  385.40
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0547661968{txt}{col 55}Centered R2   = {res}  0.8512
{txt}Total (uncentered) SS   = {res} .0548667361{txt}{col 55}Uncentered R2 = {res}  0.8514
{txt}Residual SS             = {res} .0081507008{txt}{col 55}Root MSE      = {res}  .01003

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2}  .396698{col 32}{space 2} .1024637{col 43}{space 1}    3.87{col 52}{space 3}0.000{col 60}{space 4} .1928275{col 73}{space 3} .6005685
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .4306614{col 32}{space 2} .0916906{col 43}{space 1}    4.70{col 52}{space 3}0.000{col 60}{space 4} .2482258{col 73}{space 3} .6130969
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .0257166{col 32}{space 2}  .145199{col 43}{space 1}    0.18{col 52}{space 3}0.860{col 60}{space 4}-.2631838{col 73}{space 3} .3146169
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .0461139{col 32}{space 2} .0451877{col 43}{space 1}    1.02{col 52}{space 3}0.311{col 60}{space 4}-.0437956{col 73}{space 3} .1360233
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2}-.0000943{col 32}{space 2} .0472733{col 43}{space 1}   -0.00{col 52}{space 3}0.998{col 60}{space 4}-.0941534{col 73}{space 3} .0939648
{txt}{space 12}ROLC_3 {c |}{col 20}{res}{space 2} .0199492{col 32}{space 2} .0508218{col 43}{space 1}    0.39{col 52}{space 3}0.696{col 60}{space 4}-.0811703{col 73}{space 3} .1210687
{txt}{space 12}ROLC_4 {c |}{col 20}{res}{space 2}-.0413841{col 32}{space 2} .0636946{col 43}{space 1}   -0.65{col 52}{space 3}0.518{col 60}{space 4}-.1681163{col 73}{space 3} .0853481
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0813141{col 32}{space 2} .0308768{col 43}{space 1}    2.63{col 52}{space 3}0.010{col 60}{space 4}  .019879{col 73}{space 3} .1427493
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0425569{col 32}{space 2} .0314519{col 43}{space 1}    1.35{col 52}{space 3}0.180{col 60}{space 4}-.0200225{col 73}{space 3} .1051363
{txt}{space 12}pi_w_3 {c |}{col 20}{res}{space 2}-.0142844{col 32}{space 2} .0432721{col 43}{space 1}   -0.33{col 52}{space 3}0.742{col 60}{space 4}-.1003824{col 73}{space 3} .0718135
{txt}{space 12}pi_w_4 {c |}{col 20}{res}{space 2} .0230873{col 32}{space 2} .0371918{col 43}{space 1}    0.62{col 52}{space 3}0.536{col 60}{space 4}-.0509126{col 73}{space 3} .0970873
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1182056{col 32}{space 2} .0336941{col 43}{space 1}    3.51{col 52}{space 3}0.001{col 60}{space 4} .0511649{col 73}{space 3} .1852463
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0739956{col 32}{space 2} .0615131{col 43}{space 1}    1.20{col 52}{space 3}0.233{col 60}{space 4}-.0483962{col 73}{space 3} .1963873
{txt}{space 11}pi_pc_3 {c |}{col 20}{res}{space 2} .0158017{col 32}{space 2} .0394603{col 43}{space 1}    0.40{col 52}{space 3}0.690{col 60}{space 4}-.0627118{col 73}{space 3} .0943153
{txt}{space 11}pi_pc_4 {c |}{col 20}{res}{space 2}-.0178733{col 32}{space 2} .0506015{col 43}{space 1}   -0.35{col 52}{space 3}0.725{col 60}{space 4}-.1185544{col 73}{space 3} .0828078
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0033041{col 32}{space 2} .0035465{col 43}{space 1}    0.93{col 52}{space 3}0.354{col 60}{space 4}-.0037523{col 73}{space 3} .0103605
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2}-.0027964{col 32}{space 2}  .002396{col 43}{space 1}   -1.17{col 52}{space 3}0.247{col 60}{space 4}-.0075637{col 73}{space 3} .0019708
{txt}longshort_spread_3 {c |}{col 20}{res}{space 2} .0005889{col 32}{space 2} .0021206{col 43}{space 1}    0.28{col 52}{space 3}0.782{col 60}{space 4}-.0036305{col 73}{space 3} .0048082
{txt}longshort_spread_4 {c |}{col 20}{res}{space 2} .0021237{col 32}{space 2} .0023607{col 43}{space 1}    0.90{col 52}{space 3}0.371{col 60}{space 4}-.0025733{col 73}{space 3} .0068207
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2}  .097223{col 32}{space 2} .1293409{col 43}{space 1}    0.75{col 52}{space 3}0.454{col 60}{space 4}-.1601248{col 73}{space 3} .3545707
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} .0373436{col 32}{space 2} .1379088{col 43}{space 1}    0.27{col 52}{space 3}0.787{col 60}{space 4}-.2370515{col 73}{space 3} .3117388
{txt}{space 2}logy_detrended_3 {c |}{col 20}{res}{space 2} .0168878{col 32}{space 2} .1819306{col 43}{space 1}    0.09{col 52}{space 3}0.926{col 60}{space 4} -.345097{col 73}{space 3} .3788726
{txt}{space 2}logy_detrended_4 {c |}{col 20}{res}{space 2}-.0353119{col 32}{space 2} .1325363{col 43}{space 1}   -0.27{col 52}{space 3}0.791{col 60}{space 4}-.2990177{col 73}{space 3} .2283938
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 ROLC_3 ROLC_4
{col 23}pi_w_1 pi_w_2 pi_w_3 pi_w_4 pi_pc_1 pi_pc_2 pi_pc_3
{col 23}pi_pc_4 longshort_spread_1 longshort_spread_2
{col 23}longshort_spread_3 longshort_spread_4 logy_detrended_1
{col 23}logy_detrended_2 logy_detrended_3 logy_detrended_4
{hline 78}
F test of excluded instruments:
  F( 23,    81) = {res}  385.40
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 21,    81) = {res}    8.77
{txt}  Prob > F      = {res}  0.0000



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 23{txt},{res}    81{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 21{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 21{txt},{res}    81{txt})
{res}ROLC_out    {col 14}{txt}|{col 18}{res}   98.78{col 28}  0.0000{col 37}{txt}|{col 42}{res} 2487.56{col 51}  0.0000{col 60}{txt}|{col 65}{res}   92.26
pi_hat_1    {col 14}{txt}|{col 18}{res}  349.34{col 28}  0.0000{col 37}{txt}|{col 42}{res}  361.28{col 51}  0.0000{col 60}{txt}|{col 65}{res}   13.40
pi_hat_F1   {col 14}{txt}|{col 18}{res}  385.40{col 28}  0.0000{col 37}{txt}|{col 42}{res}  236.35{col 51}  0.0000{col 60}{txt}|{col 65}{res}    8.77

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.41
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.44
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.26
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.46
{txt}{col 36}10% maximal IV size{res}{col 67} 64.69
{txt}{col 36}15% maximal IV size{res}{col 67} 33.97
{txt}{col 36}20% maximal IV size{res}{col 67} 23.50
{txt}{col 36}25% maximal IV size{res}{col 67} 18.20
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}21{txt})={res}6.38   {col 61}{txt}P-val={res}0.9991

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    0.85
Kleibergen-Paap Wald rk F statistic{col 65}    5.09

{txt}Stock-Yogo weak ID test critical values for K1=3 and L1=23:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 19.86
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 10.68
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  5.92
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.25
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}23{txt},{res}81{txt})={col 49}{res} 227.44{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}23{txt})={col 49}{res}6716.43{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}23{txt})={col 49}{res}   5.74{col 61}{txt}P-val={res}0.9999

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       104
{txt}Number of regressors                 K  = {res}         3
{txt}Number of endogenous regressors      K1 = {res}         3
{txt}Number of instruments                L  = {res}        23
{txt}Number of excluded instruments       L1 = {res}        23

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=20
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F(  3,   101) = {res} 4416.22
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0543417583{txt}{col 55}Centered R2   = {res}  0.8427
{txt}Total (uncentered) SS   = {res} .0544151079{txt}{col 55}Uncentered R2 = {res}  0.8429
{txt}Residual SS             = {res}  .008550105{txt}{col 55}Root MSE      = {res} .009067

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2} .0305493{col 26}{space 2} .0101626{col 37}{space 1}    3.01{col 46}{space 3}0.003{col 54}{space 4} .0106309{col 67}{space 3} .0504676
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .5893624{col 26}{space 2} .0520418{col 37}{space 1}   11.32{col 46}{space 3}0.000{col 54}{space 4} .4873623{col 67}{space 3} .6913626
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .4089333{col 26}{space 2} .0548323{col 37}{space 1}    7.46{col 46}{space 3}0.000{col 54}{space 4} .3014639{col 67}{space 3} .5164026
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ivregress gmm   pi_hat ( ROLC_out pi_hat_1 pi_hat_F1=  pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant wmatrix(hac nwest optimal)
{res}
{txt}{col 1}Instrumental variables (GMM) regression{col 56}Number of obs{col 70}= {res}    104
{txt}{col 1}{col 56}Wald chi2({res}3{txt}){col 70}={res}       .
{txt}{col 1}{col 56}Prob > chi2{col 70}= {res}      .
{txt}{col 1}{col 56}R-squared{col 70}={res}       .
{txt}{col 1}GMM weight matrix: HAC Bartlett 14    {col 56}Root MSE{col 70}= {res} .00916

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}      HAC
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2} .0495945{col 26}{space 2} .0203634{col 37}{space 1}    2.44{col 46}{space 3}0.015{col 54}{space 4} .0096829{col 67}{space 3} .0895061
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .6196962{col 26}{space 2} .0996239{col 37}{space 1}    6.22{col 46}{space 3}0.000{col 54}{space 4} .4244369{col 67}{space 3} .8149555
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .3751991{col 26}{space 2}  .105786{col 37}{space 1}    3.55{col 46}{space 3}0.000{col 54}{space 4} .1678624{col 67}{space 3} .5825357
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 15 22}Instrumented:{space 2}ROLC_out pi_hat_1 pi_hat_F1{p_end}
{p 0 15 22}Instruments:{space 3}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2{p_end}
HAC VCE:{col 16}Bartlett kernel with 16 lags
HAC Lags:{col 16}Chosen by Newey-West method
WMat Lags:{col 16}Chosen by Newey-West method

{com}. 
. estat overid

{txt}{col 3}Test of overidentifying restriction:

{col 3}Hansen's J chi2({res}10{txt}) ={res} 6.17399{txt} (p = {res}0.8004{txt})

{com}. 
. matrix list e(V)
{res}
{txt}symmetric e(V)[3,3]
             ROLC_out    pi_hat_1   pi_hat_F1
 ROLC_out {res}  .00041467
{txt} pi_hat_1 {res}  .00128672   .00992492
{txt}pi_hat_F1 {res}  -.0014142  -.01041034   .01119067
{reset}
{com}. 
. ivreg2  pi_hat ( ROLC_out pi_hat_1 pi_hat_F1= pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2 pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2 logy_detrended_1 logy_detrended_2) in 123/238, noconstant robust gmm2s nofooter bw(15) first ffirst
{res}{txt}Warning: time variable {res}date{txt} has {res}8{txt} gap(s) in relevant range
{res}
{txt}First-stage regressions
{hline 23}

First-stage regression of ROLC_out:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=15
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 13,    91) = {res}   96.13
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0674280706{txt}{col 55}Centered R2   = {res}  0.5635
{txt}Total (uncentered) SS   = {res} .0674445911{txt}{col 55}Uncentered R2 = {res}  0.5636
{txt}Residual SS             = {res} .0294353311{txt}{col 55}Root MSE      = {res}  .01799

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          ROLC_out{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} -.076642{col 32}{space 2} .2278061{col 43}{space 1}   -0.34{col 52}{space 3}0.737{col 60}{space 4}-.5291508{col 73}{space 3} .3758667
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .1210643{col 32}{space 2}   .12478{col 43}{space 1}    0.97{col 52}{space 3}0.335{col 60}{space 4}-.1267959{col 73}{space 3} .3689245
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1398243{col 32}{space 2} .1457308{col 43}{space 1}    0.96{col 52}{space 3}0.340{col 60}{space 4}-.1496519{col 73}{space 3} .4293006
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .3338698{col 32}{space 2} .0756947{col 43}{space 1}    4.41{col 52}{space 3}0.000{col 60}{space 4} .1835115{col 73}{space 3} .4842281
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2} .2611907{col 32}{space 2} .0656809{col 43}{space 1}    3.98{col 52}{space 3}0.000{col 60}{space 4} .1307237{col 73}{space 3} .3916577
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0372372{col 32}{space 2} .0841184{col 43}{space 1}    0.44{col 52}{space 3}0.659{col 60}{space 4}-.1298536{col 73}{space 3} .2043281
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0323096{col 32}{space 2} .0527287{col 43}{space 1}    0.61{col 52}{space 3}0.542{col 60}{space 4}-.0724296{col 73}{space 3} .1370487
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2}-.0915743{col 32}{space 2} .0744729{col 43}{space 1}   -1.23{col 52}{space 3}0.222{col 60}{space 4}-.2395055{col 73}{space 3}  .056357
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0513585{col 32}{space 2} .0956843{col 43}{space 1}    0.54{col 52}{space 3}0.593{col 60}{space 4}-.1387067{col 73}{space 3} .2414236
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0016694{col 32}{space 2} .0034473{col 43}{space 1}    0.48{col 52}{space 3}0.629{col 60}{space 4}-.0051782{col 73}{space 3} .0085171
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0013945{col 32}{space 2} .0040462{col 43}{space 1}    0.34{col 52}{space 3}0.731{col 60}{space 4}-.0066427{col 73}{space 3} .0094316
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .4438058{col 32}{space 2} .2176199{col 43}{space 1}    2.04{col 52}{space 3}0.044{col 60}{space 4} .0115307{col 73}{space 3} .8760809
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}  -.17549{col 32}{space 2} .2586743{col 43}{space 1}   -0.68{col 52}{space 3}0.499{col 60}{space 4}-.6893146{col 73}{space 3} .3383347
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2
{col 23}pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2
{col 23}logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 13,    91) = {res}   96.13
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 11,    91) = {res}   27.65
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=15
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 13,    91) = {res}  212.03
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0517944558{txt}{col 55}Centered R2   = {res}  0.8900
{txt}Total (uncentered) SS   = {res} .0518955603{txt}{col 55}Uncentered R2 = {res}  0.8902
{txt}Residual SS             = {res} .0056993392{txt}{col 55}Root MSE      = {res} .007914

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}          pi_hat_1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .2115002{col 32}{space 2} .0837452{col 43}{space 1}    2.53{col 52}{space 3}0.013{col 60}{space 4} .0451506{col 73}{space 3} .3778498
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .2815056{col 32}{space 2}  .078584{col 43}{space 1}    3.58{col 52}{space 3}0.001{col 60}{space 4} .1254081{col 73}{space 3}  .437603
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .1672927{col 32}{space 2} .0543231{col 43}{space 1}    3.08{col 52}{space 3}0.003{col 60}{space 4} .0593865{col 73}{space 3} .2751989
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2}-.0361127{col 32}{space 2} .0338356{col 43}{space 1}   -1.07{col 52}{space 3}0.289{col 60}{space 4} -.103323{col 73}{space 3} .0310976
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2} .0672724{col 32}{space 2} .0209181{col 43}{space 1}    3.22{col 52}{space 3}0.002{col 60}{space 4} .0257212{col 73}{space 3} .1088236
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0653513{col 32}{space 2} .0281605{col 43}{space 1}    2.32{col 52}{space 3}0.023{col 60}{space 4}  .009414{col 73}{space 3} .1212886
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2} .0338323{col 32}{space 2} .0323993{col 43}{space 1}    1.04{col 52}{space 3}0.299{col 60}{space 4}-.0305248{col 73}{space 3} .0981895
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1905297{col 32}{space 2}  .038829{col 43}{space 1}    4.91{col 52}{space 3}0.000{col 60}{space 4} .1134006{col 73}{space 3} .2676588
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0728259{col 32}{space 2} .0397936{col 43}{space 1}    1.83{col 52}{space 3}0.071{col 60}{space 4}-.0062192{col 73}{space 3}  .151871
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2}-.0018108{col 32}{space 2} .0014819{col 43}{space 1}   -1.22{col 52}{space 3}0.225{col 60}{space 4}-.0047544{col 73}{space 3} .0011328
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2} .0027655{col 32}{space 2}  .001699{col 43}{space 1}    1.63{col 52}{space 3}0.107{col 60}{space 4}-.0006094{col 73}{space 3} .0061405
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} -.108027{col 32}{space 2} .1352746{col 43}{space 1}   -0.80{col 52}{space 3}0.427{col 60}{space 4}-.3767333{col 73}{space 3} .1606793
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2} .1046493{col 32}{space 2} .1497835{col 43}{space 1}    0.70{col 52}{space 3}0.487{col 60}{space 4}-.1928772{col 73}{space 3} .4021758
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2
{col 23}pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2
{col 23}logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 13,    91) = {res}  212.03
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 11,    91) = {res}   13.23
{txt}  Prob > F      = {res}  0.0000

{txt}First-stage regression of pi_hat_F1:

OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=15
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F( 13,    91) = {res}   73.84
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0547661968{txt}{col 55}Centered R2   = {res}  0.8418
{txt}Total (uncentered) SS   = {res} .0548667361{txt}{col 55}Uncentered R2 = {res}  0.8421
{txt}Residual SS             = {res} .0086657661{txt}{col 55}Root MSE      = {res} .009758

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}         pi_hat_F1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}pi_hat_2 {c |}{col 20}{res}{space 2} .3810994{col 32}{space 2} .1173257{col 43}{space 1}    3.25{col 52}{space 3}0.002{col 60}{space 4} .1480464{col 73}{space 3} .6141525
{txt}{space 10}pi_hat_3 {c |}{col 20}{res}{space 2} .4240511{col 32}{space 2} .0764453{col 43}{space 1}    5.55{col 52}{space 3}0.000{col 60}{space 4} .2722019{col 73}{space 3} .5759004
{txt}{space 10}pi_hat_4 {c |}{col 20}{res}{space 2} .0202079{col 32}{space 2} .0976801{col 43}{space 1}    0.21{col 52}{space 3}0.837{col 60}{space 4}-.1738216{col 73}{space 3} .2142374
{txt}{space 12}ROLC_1 {c |}{col 20}{res}{space 2} .0319716{col 32}{space 2} .0417915{col 43}{space 1}    0.77{col 52}{space 3}0.446{col 60}{space 4} -.051042{col 73}{space 3} .1149853
{txt}{space 12}ROLC_2 {c |}{col 20}{res}{space 2} .0076413{col 32}{space 2}  .052366{col 43}{space 1}    0.15{col 52}{space 3}0.884{col 60}{space 4}-.0963774{col 73}{space 3}   .11166
{txt}{space 12}pi_w_1 {c |}{col 20}{res}{space 2} .0678628{col 32}{space 2} .0326182{col 43}{space 1}    2.08{col 52}{space 3}0.040{col 60}{space 4} .0030707{col 73}{space 3} .1326549
{txt}{space 12}pi_w_2 {c |}{col 20}{res}{space 2}  .032739{col 32}{space 2} .0283465{col 43}{space 1}    1.15{col 52}{space 3}0.251{col 60}{space 4}-.0235679{col 73}{space 3} .0890459
{txt}{space 11}pi_pc_1 {c |}{col 20}{res}{space 2} .1013268{col 32}{space 2} .0360635{col 43}{space 1}    2.81{col 52}{space 3}0.006{col 60}{space 4} .0296911{col 73}{space 3} .1729625
{txt}{space 11}pi_pc_2 {c |}{col 20}{res}{space 2} .0801602{col 32}{space 2} .0624368{col 43}{space 1}    1.28{col 52}{space 3}0.202{col 60}{space 4}-.0438628{col 73}{space 3} .2041832
{txt}longshort_spread_1 {c |}{col 20}{res}{space 2} .0025542{col 32}{space 2} .0038773{col 43}{space 1}    0.66{col 52}{space 3}0.512{col 60}{space 4}-.0051476{col 73}{space 3} .0102559
{txt}longshort_spread_2 {c |}{col 20}{res}{space 2}-.0000418{col 32}{space 2} .0032712{col 43}{space 1}   -0.01{col 52}{space 3}0.990{col 60}{space 4}-.0065397{col 73}{space 3} .0064561
{txt}{space 2}logy_detrended_1 {c |}{col 20}{res}{space 2} .1368819{col 32}{space 2} .1228026{col 43}{space 1}    1.11{col 52}{space 3}0.268{col 60}{space 4}-.1070503{col 73}{space 3} .3808142
{txt}{space 2}logy_detrended_2 {c |}{col 20}{res}{space 2}-.0064177{col 32}{space 2} .1302246{col 43}{space 1}   -0.05{col 52}{space 3}0.961{col 60}{space 4}-.2650929{col 73}{space 3} .2522576
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}pi_hat_2 pi_hat_3 pi_hat_4 ROLC_1 ROLC_2 pi_w_1 pi_w_2
{col 23}pi_pc_1 pi_pc_2 longshort_spread_1 longshort_spread_2
{col 23}logy_detrended_1 logy_detrended_2
{hline 78}
F test of excluded instruments:
  F( 13,    91) = {res}   73.84
{txt}  Prob > F      = {res}  0.0000
{help ivreg2##apstats:Angrist-Pischke multivariate F test of excluded instruments:}
{txt}  F( 11,    91) = {res}    5.77
{txt}  Prob > F      = {res}  0.0000



{txt}Summary results for first-stage regressions
{hline 43}

{col 44}{help ivreg2##apstats:(Underid)}{col 65}{help ivreg2##apstats:(Weak id)}
Variable     |{col 16}{help ivreg2##apstats:F}({res}{col 17} 13{txt},{res}    91{txt})  P-val{col 37}|{col 39}{help ivreg2##apstats:AP Chi-sq}({res} 11{txt}) P-val{col 60}|{col 62}{help ivreg2##apstats:AP F}({res}{col 67} 11{txt},{res}    91{txt})
{res}ROLC_out    {col 14}{txt}|{col 18}{res}   96.13{col 28}  0.0000{col 37}{txt}|{col 42}{res}  347.57{col 51}  0.0000{col 60}{txt}|{col 65}{res}   27.65
pi_hat_1    {col 14}{txt}|{col 18}{res}  212.03{col 28}  0.0000{col 37}{txt}|{col 42}{res}  166.36{col 51}  0.0000{col 60}{txt}|{col 65}{res}   13.23
pi_hat_F1   {col 14}{txt}|{col 18}{res}   73.84{col 28}  0.0000{col 37}{txt}|{col 42}{res}   72.51{col 51}  0.0000{col 60}{txt}|{col 65}{res}    5.77

{txt}NB: first-stage test statistics heteroskedasticity and autocorrelation-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 21.10
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 11.51
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  6.56
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.80
{txt}{col 36}10% maximal IV size{res}{col 67} 40.90
{txt}{col 36}15% maximal IV size{res}{col 67} 22.06
{txt}{col 36}20% maximal IV size{res}{col 67} 15.56
{txt}{col 36}25% maximal IV size{res}{col 67} 12.23
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##idtest:Underidentification test}
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
{res}Kleibergen-Paap rk LM statistic{txt}{col 42}Chi-sq({res}11{txt})={res}7.54   {col 61}{txt}P-val={res}0.7541

{help ivreg2##widtest:Weak identification test}
{txt}Ho: equation is weakly identified
{res}Cragg-Donald Wald F statistic{col 65}    1.10
Kleibergen-Paap Wald rk F statistic{col 65}    3.65

{txt}Stock-Yogo weak ID test critical values for K1=3 and L1=13:
{res}{txt}{col 37}5% maximal IV relative bias{res}{col 67} 18.17
{txt}{col 36}10% maximal IV relative bias{res}{col 67} 10.14
{txt}{col 36}20% maximal IV relative bias{res}{col 67}  5.92
{txt}{col 36}30% maximal IV relative bias{res}{col 67}  4.41
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

{help ivreg2##wirobust:Weak-instrument-robust inference}
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
{res}Anderson-Rubin Wald test{txt}{col 36}F({res}13{txt},{res}91{txt})={col 49}{res} 110.57{col 61}{txt}P-val={res}0.0000
Anderson-Rubin Wald test{txt}{col 36}Chi-sq({res}13{txt})={col 49}{res}1642.74{col 61}{txt}P-val={res}0.0000
Stock-Wright LM S statistic{txt}{col 36}Chi-sq({res}13{txt})={col 49}{res}   6.03{col 61}{txt}P-val={res}0.9451

{txt}NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity and autocorrelation-robust

Number of observations               N  = {res}       104
{txt}Number of regressors                 K  = {res}         3
{txt}Number of endogenous regressors      K1 = {res}         3
{txt}Number of instruments                L  = {res}        13
{txt}Number of excluded instruments       L1 = {res}        13

{txt}2-Step GMM estimation
{hline 21}

Estimates efficient for arbitrary heteroskedasticity and autocorrelation
Statistics robust to heteroskedasticity and autocorrelation
  kernel=Bartlett; bandwidth=15
  time variable (t):  {res}date

{txt}{col 55}Number of obs = {res}     104
{txt}{col 55}F(  3,   101) = {res} 1340.57
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} .0543417583{txt}{col 55}Centered R2   = {res}  0.8395
{txt}Total (uncentered) SS   = {res} .0544151079{txt}{col 55}Uncentered R2 = {res}  0.8397
{txt}Residual SS             = {res} .0087242255{txt}{col 55}Root MSE      = {res} .009159

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}      pi_hat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}ROLC_out {c |}{col 14}{res}{space 2} .0495945{col 26}{space 2} .0206183{col 37}{space 1}    2.41{col 46}{space 3}0.016{col 54}{space 4} .0091834{col 67}{space 3} .0900056
{txt}{space 4}pi_hat_1 {c |}{col 14}{res}{space 2} .6196962{col 26}{space 2} .1071949{col 37}{space 1}    5.78{col 46}{space 3}0.000{col 54}{space 4} .4095981{col 67}{space 3} .8297943
{txt}{space 3}pi_hat_F1 {c |}{col 14}{res}{space 2} .3751991{col 26}{space 2} .1140812{col 37}{space 1}    3.29{col 46}{space 3}0.001{col 54}{space 4} .1516041{col 67}{space 3}  .598794
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. twoway (line ROLC date, lpattern(dash)) (line ROLC_out date, cmissing(n)) in 123/238
{res}{txt}
{com}. 
. sum ROLC_out in 123/238

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 4}ROLC_out {c |}{res}       104    .0003986     .025586  -.0455346   .0459672
{txt}
{com}. 
. regress delta_pi_hat_F1 RULC in 123/238, noconstant

      {txt}Source {c |}       SS       df       MS              Number of obs ={res}     116
{txt}{hline 13}{char +}{hline 30}           F(  1,   115) ={res}    0.18
    {txt}   Model {char |} {res} .000020149     1  .000020149           {txt}Prob > F      = {res} 0.6683
    {txt}Residual {char |} {res} .012553014   115  .000109157           {txt}R-squared     = {res} 0.0016
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res}-0.0071
    {txt}   Total {char |} {res} .012573163   116  .000108389           {txt}Root MSE      = {res} .01045

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}delta_pi_~F1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}RULC {c |}{col 14}{res}{space 2} .0193325{col 26}{space 2} .0449971{col 37}{space 1}    0.43{col 46}{space 3}0.668{col 54}{space 4}-.0697981{col 67}{space 3} .1084631
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. regress delta_pi_hat_F1 ROLC in 123/238, noconstant

      {txt}Source {c |}       SS       df       MS              Number of obs ={res}     116
{txt}{hline 13}{char +}{hline 30}           F(  1,   115) ={res}    3.29
    {txt}   Model {char |} {res} .000349317     1  .000349317           {txt}Prob > F      = {res} 0.0725
    {txt}Residual {char |} {res} .012223846   115  .000106294           {txt}R-squared     = {res} 0.0278
{txt}{hline 13}{char +}{hline 30}           Adj R-squared = {res} 0.0193
    {txt}   Total {char |} {res} .012573163   116  .000108389           {txt}Root MSE      = {res} .01031

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}delta_pi_~F1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}ROLC {c |}{col 14}{res}{space 2}-.0569195{col 26}{space 2} .0313983{col 37}{space 1}   -1.81{col 46}{space 3}0.072{col 54}{space 4}-.1191135{col 67}{space 3} .0052745
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}\\isad.isadroot.ex.ac.uk\uoe\user\Submitted New Keynesian Model with Overtime Labor\Referee reports RESTAT\reports 2nd round\Files for RESTAT\NKPC_gmm_robustness.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}19 May 2012, 11:51:42
{txt}{.-}
{smcl}
{txt}{sf}{ul off}